(* Content-type: application/vnd.wolfram.mathematica *)

(*** Wolfram Notebook File ***)
(* http://www.wolfram.com/nb *)

(* CreatedBy='Mathematica 9.0' *)

(*CacheID: 234*)
(* Internal cache information:
NotebookFileLineBreakTest
NotebookFileLineBreakTest
NotebookDataPosition[       157,          7]
NotebookDataLength[   1200095,      23717]
NotebookOptionsPosition[   1189756,      23406]
NotebookOutlinePosition[   1190111,      23422]
CellTagsIndexPosition[   1190068,      23419]
WindowFrame->Normal*)

(* Beginning of Notebook Content *)
Notebook[{

Cell[CellGroupData[{
Cell[BoxData[
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{
       RowBox[{"a", " ", 
        RowBox[{"Cos", "[", "t", "]"}]}], "+", 
       RowBox[{"0.5", "b", " ", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{"Cos", "[", 
           RowBox[{"2", " ", "t"}], "]"}], "-", "1"}], ")"}]}]}], ",", 
      RowBox[{"c", " ", 
       RowBox[{"Sin", "[", " ", "t", "]"}]}]}], "}"}], "/.", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{"a", "\[Rule]", "1"}], ",", 
      RowBox[{"b", "\[Rule]", "1.3"}], ",", 
      RowBox[{"c", "\[Rule]", "1.5"}]}], "}"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"3", "*", "\[Pi]"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.61115108640484*^9, 3.611151310990012*^9}, {
   3.6111513436876698`*^9, 3.611151388384706*^9}, {3.611151469689024*^9, 
   3.6111516865784473`*^9}, {3.611151743543281*^9, 3.611151764762981*^9}, {
   3.6111544440146523`*^9, 3.6111545630874367`*^9}, {3.611154612116784*^9, 
   3.611154677501274*^9}, {3.611154748137321*^9, 3.611154758284789*^9}, {
   3.611154791577311*^9, 3.611154791697352*^9}, {3.6111550895740833`*^9, 
   3.6111550952203608`*^9}, {3.6111552118165216`*^9, 3.611155217848283*^9}, 
   3.6111552520676937`*^9, 3.61115530746484*^9, {3.611155340208496*^9, 
   3.6111553798983097`*^9}, {3.611155414442937*^9, 3.611155452318412*^9}, {
   3.611155540692247*^9, 3.611155600771031*^9}, {3.6111556817031107`*^9, 
   3.611155687698292*^9}, {3.611156217137864*^9, 3.61115628926678*^9}, {
   3.611156658053341*^9, 3.611156715447525*^9}, {3.611156782768681*^9, 
   3.6111567828304873`*^9}, {3.611157054639423*^9, 3.611157054733473*^9}, {
   3.611157087037763*^9, 3.611157087117962*^9}, {3.611157151478784*^9, 
   3.6111571569467897`*^9}, {3.611158228636106*^9, 3.611158247450526*^9}, {
   3.611158342532736*^9, 3.6111583930746326`*^9}, {3.611158467141286*^9, 
   3.611158504528286*^9}, {3.611158609933433*^9, 3.611158712384643*^9}, {
   3.611170864430879*^9, 3.611170873482126*^9}, {3.611288313563306*^9, 
   3.611288313931353*^9}, {3.612976455805603*^9, 3.6129764684111633`*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw0m3lYju/TxpEsRSVbpWQJISGKUKNUQtooIYlKiyQJlaSSSlJaRdkqtEl7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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-1.4923076569037035`, 1.}, {-1.499999605581218, 
   1.4999985833099596`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.611151278909131*^9, 3.611151311671433*^9}, {
   3.611151344742135*^9, 3.611151389173709*^9}, {3.611151471589355*^9, 
   3.61115168703378*^9}, {3.6111517441825323`*^9, 3.6111517651629343`*^9}, {
   3.6111544444546432`*^9, 3.6111545637099648`*^9}, {3.6111546131078663`*^9, 
   3.6111546782658157`*^9}, {3.611154748779118*^9, 3.611154792100338*^9}, {
   3.611155090004496*^9, 3.611155095626698*^9}, {3.611155212792589*^9, 
   3.6111552183373957`*^9}, 3.6111552528914433`*^9, 3.611155308792075*^9, {
   3.6111553407680073`*^9, 3.6111553802222347`*^9}, 3.611155452733048*^9, {
   3.611155541274702*^9, 3.611155601893361*^9}, {3.6111556823969*^9, 
   3.611155688824798*^9}, {3.611156217865844*^9, 3.611156291617179*^9}, {
   3.611156658658188*^9, 3.611156716772356*^9}, 3.611156783820366*^9, 
   3.611157055187098*^9, 3.611157087475398*^9, {3.611157152206748*^9, 
   3.611157157479463*^9}, {3.611158232918429*^9, 3.611158248345436*^9}, {
   3.611158343071814*^9, 3.611158393885157*^9}, {3.6111584677192087`*^9, 
   3.6111584748776703`*^9}, 3.611158505043762*^9, {3.611158614397113*^9, 
   3.611158712816639*^9}, 3.6111708745986853`*^9, 3.6112883172593937`*^9, {
   3.612976459526813*^9, 3.612976469388908*^9}}]
}, Open  ]],

Cell[BoxData[{
 RowBox[{"A", "-", "wigth"}], "\[IndentingNewLine]", 
 RowBox[{"D", " ", "-", " ", "height"}], "\[IndentingNewLine]", 
 RowBox[{"C", "-", "offset"}], "\[IndentingNewLine]", "ArcTan"}], "Input",
 CellChangeTimes->{{3.6111547000614357`*^9, 3.6111547228104057`*^9}, {
  3.611154775257197*^9, 3.611154778606412*^9}, {3.6111554306565847`*^9, 
  3.611155435670574*^9}, {3.611332931867968*^9, 3.6113329456944017`*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{
    FractionBox[
     RowBox[{"1.5", 
      RowBox[{"Sin", "[", "t", "]"}]}], 
     RowBox[{
      RowBox[{"Cos", "[", "t", "]"}], "+", 
      RowBox[{"0.67", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"2", " ", "t"}], "]"}], "-", "1"}], ")"}]}]}]], ",", "t"}], 
   "]"}], "/.", 
  RowBox[{"t", "\[Rule]", 
   RowBox[{"\[Pi]", "-", 
    RowBox[{"1", "e"}], "-", "10"}]}]}]], "Input",
 CellChangeTimes->{{3.6112913080654507`*^9, 3.611291315162623*^9}, {
  3.611332860919072*^9, 3.6113329064408827`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", 
   FractionBox[
    RowBox[{"1.5`", " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"10", "+", "e"}], "]"}]}], 
    RowBox[{
     RowBox[{"-", 
      RowBox[{"Cos", "[", 
       RowBox[{"10", "+", "e"}], "]"}]}], "+", 
     RowBox[{"0.67`", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", 
        RowBox[{"Cos", "[", 
         RowBox[{"2", " ", 
          RowBox[{"(", 
           RowBox[{
            RowBox[{"-", "10"}], "-", "e", "+", "\[Pi]"}], ")"}]}], "]"}]}], 
       ")"}]}]}]]}], "-", 
  FractionBox[
   RowBox[{"1.5`", " ", 
    RowBox[{"Sin", "[", 
     RowBox[{"10", "+", "e"}], "]"}], " ", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"-", 
       RowBox[{"Sin", "[", 
        RowBox[{"10", "+", "e"}], "]"}]}], "-", 
      RowBox[{"1.34`", " ", 
       RowBox[{"Sin", "[", 
        RowBox[{"2", " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{"-", "10"}], "-", "e", "+", "\[Pi]"}], ")"}]}], "]"}]}]}], 
     ")"}]}], 
   SuperscriptBox[
    RowBox[{"(", 
     RowBox[{
      RowBox[{"-", 
       RowBox[{"Cos", "[", 
        RowBox[{"10", "+", "e"}], "]"}]}], "+", 
      RowBox[{"0.67`", " ", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "1"}], "+", 
         RowBox[{"Cos", "[", 
          RowBox[{"2", " ", 
           RowBox[{"(", 
            RowBox[{
             RowBox[{"-", "10"}], "-", "e", "+", "\[Pi]"}], ")"}]}], "]"}]}], 
        ")"}]}]}], ")"}], "2"]]}]], "Output",
 CellChangeTimes->{3.611291315729793*^9, 3.611332874445149*^9, 
  3.611332907606164*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Arg", "[", 
    RowBox[{
     RowBox[{"Cos", "[", "t", "]"}], "+", 
     RowBox[{"0.67", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"Cos", "[", 
         RowBox[{"2", " ", "t"}], "]"}], "-", "1"}], ")"}]}], "+", 
     RowBox[{"\[ImaginaryI]", " ", "1.5", 
      RowBox[{"Sin", "[", "t", "]"}]}]}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", 
     RowBox[{"-", "\[Pi]"}], ",", 
     RowBox[{"\[Pi]", "+", "1"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.611291178830667*^9, 3.611291257513144*^9}, {
  3.611332991493561*^9, 3.611333032247504*^9}, {3.611333223889957*^9, 
  3.611333224832378*^9}}],

Cell[BoxData[
 GraphicsBox[{{{}, {}, 
    {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVVHk4ld0Xvfd93ztRyZBGvlSGqIjSJOeIhGQoolQqURISyVChLxooGSL5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      "]], LineBox[CompressedData["
1:eJwVlGs0lAkcxvG+c3nnncu7s+iiREu1R1urwUbJfxrHpSWMjU1URiY7q11L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      "]]}, {}}, {{}, {}, {}}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->
   NCache[{{-Pi, 1 + Pi}, {-3.141592430635141, 
     3.138109020155558}}, {{-3.141592653589793, 
    4.141592653589793}, {-3.141592430635141, 3.138109020155558}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.611291252559651*^9, 3.611291260265423*^9}, {
   3.611333014056157*^9, 3.6113330327282057`*^9}, 
   3.61133322635738*^9},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"Cos", "[", 
    RowBox[{"2", "t"}], "]"}], "\[Equal]", 
   RowBox[{
    RowBox[{"2", 
     SuperscriptBox[
      RowBox[{"Cos", "[", "t", "]"}], "2"]}], "-", "1"}]}], "//", 
  "Simplify"}]], "Input",
 CellChangeTimes->{{3.611155696373474*^9, 3.611155731234173*^9}, {
  3.61115576210651*^9, 3.611155772575388*^9}, {3.611157181510915*^9, 
  3.6111572124298077`*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{{3.611155715725438*^9, 3.611155731910098*^9}, {
  3.61115576631022*^9, 3.611155773186908*^9}, {3.611157186600008*^9, 
  3.611157212854619*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{
       RowBox[{"a", " ", 
        RowBox[{"Cos", "[", "t", "]"}]}], "+", 
       RowBox[{"b", " ", 
        RowBox[{"(", 
         RowBox[{
          SuperscriptBox[
           RowBox[{"Cos", "[", "t", "]"}], "2"], "-", "1"}], ")"}]}]}], ",", 
      RowBox[{"d", " ", 
       RowBox[{"Sin", "[", " ", "t", "]"}]}]}], "}"}], "/.", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{"a", "\[Rule]", "1"}], ",", 
      RowBox[{"b", "\[Rule]", "3"}], ",", 
      RowBox[{"c", "\[Rule]", 
       RowBox[{"-", "0.65"}]}], ",", 
      RowBox[{"d", "\[Rule]", "1.05"}]}], "}"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.6111560109365053`*^9, 3.611156016525663*^9}, {
  3.611156173448202*^9, 3.611156199888688*^9}, {3.6111572446669407`*^9, 
  3.61115730153104*^9}, {3.6111573451173964`*^9, 3.6111573674255447`*^9}, {
  3.611157421399661*^9, 3.611157499023295*^9}, {3.611157870415339*^9, 
  3.6111578800822*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw12nc4l9/7AHAj3o8kKpSMEKUokUqSU9JAg1AihawIpRBJNmVkU/bemams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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-3.0833321656260253`, 1.}, {-1.049999852245265, 
   1.0499998721882131`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{
  3.611156017356599*^9, {3.6111561740673113`*^9, 3.611156200254941*^9}, {
   3.6111572663891373`*^9, 3.611157303126051*^9}, {3.6111573536635723`*^9, 
   3.611157368573531*^9}, {3.611157423235674*^9, 3.611157499386239*^9}, {
   3.611157871334285*^9, 3.611157880926566*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"a", " ", 
    RowBox[{"Cos", "[", "t", "]"}]}], "+", 
   RowBox[{"0.5", "b", " ", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"Cos", "[", 
       RowBox[{"2", " ", "t"}], "]"}], "-", "1"}], ")"}]}]}], "//", 
  "TrigReduce"}]], "Input",
 CellChangeTimes->{{3.6111588928000307`*^9, 3.6111588948199587`*^9}, {
  3.611158938863061*^9, 3.6111589459990788`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"-", "0.5`"}], " ", "b"}], "+", 
  RowBox[{"a", " ", 
   RowBox[{"Cos", "[", "t", "]"}]}], "+", 
  RowBox[{"0.5`", " ", "b", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"2", " ", "t"}], "]"}]}]}]], "Output",
 CellChangeTimes->{3.611158895385923*^9, 3.611158947262154*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  SuperscriptBox[
   RowBox[{"(", 
    RowBox[{
     SuperscriptBox[
      RowBox[{"Cos", "[", 
       FractionBox["t", "2"], "]"}], "2"], "+", 
     SuperscriptBox[
      RowBox[{"Sin", "[", 
       FractionBox["t", "2"], "]"}], "2"]}], ")"}], 
   RowBox[{"1", "/", "2"}]], "//", "Simplify"}]], "Input",
 CellChangeTimes->{{3.612110508580061*^9, 3.6121105441243277`*^9}}],

Cell[BoxData["1"], "Output",
 CellChangeTimes->{{3.612110523726997*^9, 3.612110544858732*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"Sin", "[", 
   RowBox[{
    RowBox[{"t", "/", "2"}], "+", 
    RowBox[{"\[Pi]", "/", "4"}]}], "]"}], "//", "TrigExpand"}]], "Input",
 CellChangeTimes->{{3.612109506915103*^9, 3.612109527912277*^9}, {
  3.612110562629732*^9, 3.6121105805906973`*^9}}],

Cell[BoxData[
 RowBox[{
  FractionBox[
   RowBox[{"Cos", "[", 
    FractionBox["t", "2"], "]"}], 
   SqrtBox["2"]], "+", 
  FractionBox[
   RowBox[{"Sin", "[", 
    FractionBox["t", "2"], "]"}], 
   SqrtBox["2"]]}]], "Output",
 CellChangeTimes->{
  3.612110177975362*^9, {3.612110567576206*^9, 3.6121105813678093`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"1.", "/", 
  SqrtBox["2"]}]], "Input",
 CellChangeTimes->{{3.612109959614213*^9, 3.612109976335012*^9}}],

Cell[BoxData["0.7071067811865475`"], "Output",
 CellChangeTimes->{{3.6121099728613853`*^9, 3.612109977223736*^9}}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{
   SuperscriptBox[
    RowBox[{"(", 
     FractionBox[
      RowBox[{
       RowBox[{"Cos", "[", 
        RowBox[{"t", "/", "2"}], "]"}], "+", 
       RowBox[{"Sin", "[", 
        RowBox[{"t", "/", "2"}], "]"}]}], 
      SqrtBox["2"]], ")"}], "20"], "\[Equal]", "0"}], "//", 
  "Reduce"}]], "Input",
 CellChangeTimes->{{3.612116901522793*^9, 3.612116914060803*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"Cos", "[", 
      FractionBox["t", "2"], "]"}], ",", 
     RowBox[{"Sin", "[", 
      FractionBox["t", "2"], "]"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.612116930535187*^9, 3.612116972161893*^9}, 
   3.612117977470521*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwt1wk0lssfB3BbtlKI931eCtEiW3WRhH6TZL0JXSlLllKoiEq3km4q2kSW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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJwd2Hk4Vd/3B3Au7j3nojJ2hQbNEkmRDGvxqRRlqjTIWEpSpkIlUlJRQpJk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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->
   NCache[{{0, 2 Pi}, {-0.9999999999999979, 0.9999999999999979}}, {{
     0, 6.283185307179586}, {-0.9999999999999979, 0.9999999999999979}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{3.612116972812627*^9, 3.612117977882161*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{"1", "+", 
     RowBox[{"0.6", 
      RowBox[{"(", 
       RowBox[{"1", "-", 
        RowBox[{"Tanh", "[", 
         RowBox[{"100", 
          RowBox[{"(", 
           RowBox[{"t", "-", "\[Pi]"}], ")"}]}], "]"}]}], ")"}], 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "200"]}]}], ")"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"1", "+", 
    RowBox[{"2", 
     SuperscriptBox[
      RowBox[{"(", 
       FractionBox[
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"t", "/", "2"}], "]"}], "+", 
         RowBox[{"Cos", "[", 
          RowBox[{"t", "/", "2"}], "]"}]}], 
        SqrtBox["2"]], ")"}], "20"]}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{"1", "+", 
     SuperscriptBox[
      RowBox[{"(", 
       FractionBox[
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"t", "/", "2"}], "]"}], "+", 
         RowBox[{"Sin", "[", 
          RowBox[{"t", "/", "2"}], "]"}]}], 
        SqrtBox["2"]], ")"}], "20"]}], ")"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.6121090023627243`*^9, 3.612109071875289*^9}, {
   3.612109113797434*^9, 3.612109131118078*^9}, {3.6121091833663*^9, 
   3.6121091873328037`*^9}, {3.612109232252639*^9, 3.612109260230188*^9}, {
   3.612109311519319*^9, 3.6121093698556833`*^9}, {3.6121095841624613`*^9, 
   3.612109651281622*^9}, {3.612109716286483*^9, 3.612109716373358*^9}, {
   3.612109793524828*^9, 3.612109918699689*^9}, {3.612109989395602*^9, 
   3.612110056180992*^9}, {3.6121101131958*^9, 3.612110119744402*^9}, {
   3.61211019117817*^9, 3.612110192184883*^9}, {3.612110601605851*^9, 
   3.612110613325885*^9}, {3.6121109671216993`*^9, 3.612111020654414*^9}, {
   3.612112010849716*^9, 3.612112048556734*^9}, {3.612116197746169*^9, 
   3.612116235759964*^9}, 3.612116893100602*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJxF2HlUTP//B/CZpj3RJg3Rqn3hQyUtrytEaVOpaCMkicpSKksllSKKVlGo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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 1.},
  Method->{},
  PlotRange->
   NCache[{{0, 2 Pi}, {1., 2.1999707710449847`}}, {{0, 6.283185307179586}, {
     1., 2.1999707710449847`}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.612109014732848*^9, 3.612109041059553*^9}, 
   3.6121091255256767`*^9, 3.612109187851563*^9, {3.6121092378623123`*^9, 
   3.6121092608702374`*^9}, {3.612109312610273*^9, 3.61210937031565*^9}, {
   3.6121095971730537`*^9, 3.612109652705051*^9}, 3.612109717229126*^9, {
   3.612109794165872*^9, 3.61210991929268*^9}, {3.612109993358667*^9, 
   3.6121100566021843`*^9}, {3.612110114018425*^9, 3.61211012017871*^9}, 
   3.6121101927919073`*^9, {3.612110605069701*^9, 3.6121106140253687`*^9}, {
   3.612110968532237*^9, 3.612111021656404*^9}, {3.612112012132163*^9, 
   3.6121120490407*^9}, {3.612116207958191*^9, 3.6121162365411453`*^9}, 
   3.613439254685709*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJxF2Hk8VUH7AHD7vZZrd+8VIRVSqCgSzUNCESJL2UqkFCFbJZWE0KYSKio7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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 1.},
  Method->{},
  PlotRange->
   NCache[{{0, 2 Pi}, {1., 2.9999987821124448`}}, {{0, 6.283185307179586}, {
     1., 2.9999987821124448`}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.612109014732848*^9, 3.612109041059553*^9}, 
   3.6121091255256767`*^9, 3.612109187851563*^9, {3.6121092378623123`*^9, 
   3.6121092608702374`*^9}, {3.612109312610273*^9, 3.61210937031565*^9}, {
   3.6121095971730537`*^9, 3.612109652705051*^9}, 3.612109717229126*^9, {
   3.612109794165872*^9, 3.61210991929268*^9}, {3.612109993358667*^9, 
   3.6121100566021843`*^9}, {3.612110114018425*^9, 3.61211012017871*^9}, 
   3.6121101927919073`*^9, {3.612110605069701*^9, 3.6121106140253687`*^9}, {
   3.612110968532237*^9, 3.612111021656404*^9}, {3.612112012132163*^9, 
   3.6121120490407*^9}, {3.612116207958191*^9, 3.6121162365411453`*^9}, 
   3.61343925474358*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJxF2Hk4VVHXAHDzfGW89yoJDSRDg9KAtRJpkESkMidjxgwlSRPShEYiRYYo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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 1.},
  Method->{},
  PlotRange->
   NCache[{{0, 2 Pi}, {1., 1.9999993910562224`}}, {{0, 6.283185307179586}, {
     1., 1.9999993910562224`}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.612109014732848*^9, 3.612109041059553*^9}, 
   3.6121091255256767`*^9, 3.612109187851563*^9, {3.6121092378623123`*^9, 
   3.6121092608702374`*^9}, {3.612109312610273*^9, 3.61210937031565*^9}, {
   3.6121095971730537`*^9, 3.612109652705051*^9}, 3.612109717229126*^9, {
   3.612109794165872*^9, 3.61210991929268*^9}, {3.612109993358667*^9, 
   3.6121100566021843`*^9}, {3.612110114018425*^9, 3.61211012017871*^9}, 
   3.6121101927919073`*^9, {3.612110605069701*^9, 3.6121106140253687`*^9}, {
   3.612110968532237*^9, 3.612111021656404*^9}, {3.612112012132163*^9, 
   3.6121120490407*^9}, {3.612116207958191*^9, 3.6121162365411453`*^9}, 
   3.613439254757806*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"1.8", "/", "5"}], " ", 
   RowBox[{"Sin", "[", "t", "]"}], 
   RowBox[{"(", 
    RowBox[{"1", "+", 
     SuperscriptBox[
      RowBox[{"(", 
       FractionBox[
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"t", "/", "2"}], "]"}], "+", 
         RowBox[{"Sin", "[", 
          RowBox[{"t", "/", "2"}], "]"}]}], 
        SqrtBox["2"]], ")"}], "200"]}], ")"}]}], "/.", 
  RowBox[{"t", "\[Rule]", 
   RowBox[{"3", 
    RowBox[{"\[Pi]", "/", "4"}]}]}]}]], "Input",
 CellChangeTimes->{{3.6121539183407507`*^9, 3.6121539469860373`*^9}}],

Cell[BoxData["0.25455847502248674`"], "Output",
 CellChangeTimes->{{3.612153931678978*^9, 3.612153947494504*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"1.8", "/", "5"}], " ", 
      RowBox[{"Sin", "[", "t", "]"}], 
      RowBox[{"(", 
       RowBox[{"1", "+", 
        RowBox[{"2", 
         SuperscriptBox[
          RowBox[{"(", 
           FractionBox[
            RowBox[{
             RowBox[{"Cos", "[", 
              RowBox[{"t", "/", "2"}], "]"}], "+", 
             RowBox[{"Sin", "[", 
              RowBox[{"t", "/", "2"}], "]"}]}], 
            SqrtBox["2"]], ")"}], "150"]}]}], ")"}]}], ",", 
     RowBox[{"-", "0.4"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.613851634729348*^9, 3.613851678384954*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVmXk4VG8bxye7UObMKFLWRNmqn0LhfqjQJpEoilQqUpbKmqJCmySREpIt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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJxTTMoPSmViYGAwAWIQzbyf69xj00a7WTNB4Ob+oBzJWzMmrbeH8Sd+itk8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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->
   NCache[{{0, 2 Pi}, {-0.4, 1.0799965801786193`}}, {{
     0, 6.283185307179586}, {-0.4, 1.0799965801786193`}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.613851660237937*^9, 3.613851679854191*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", 
   RowBox[{"ParametricPlot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{"Cos", "[", "t", "]"}], ",", 
       RowBox[{
        RowBox[{"1", "/", "5"}], " ", 
        RowBox[{"Sin", "[", "t", "]"}], 
        RowBox[{"(", 
         RowBox[{"1", "+", 
          RowBox[{"2", 
           SuperscriptBox[
            RowBox[{"Sin", "[", 
             RowBox[{
              RowBox[{"t", "/", "2"}], "+", 
              RowBox[{"\[Pi]", "/", "4"}]}], "]"}], "200"]}]}], ")"}]}]}], 
      "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "0", ",", 
       RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"ParametricPlot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{"{", 
        RowBox[{
         RowBox[{"1.8", 
          RowBox[{"Cos", "[", "t", "]"}]}], ",", 
         RowBox[{
          RowBox[{"1.8", "/", "5"}], " ", 
          RowBox[{"Sin", "[", "t", "]"}], 
          RowBox[{"(", 
           RowBox[{"1", "+", 
            RowBox[{"2", 
             SuperscriptBox[
              RowBox[{"(", 
               FractionBox[
                RowBox[{
                 RowBox[{"Cos", "[", 
                  RowBox[{"t", "/", "2"}], "]"}], "+", 
                 RowBox[{"Sin", "[", 
                  RowBox[{"t", "/", "2"}], "]"}]}], 
                SqrtBox["2"]], ")"}], "150"]}]}], ")"}]}]}], "}"}], ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", 
         RowBox[{"-", "0.6"}]}], "}"}], ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", "1.2"}], "}"}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "0", ",", 
       RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"ParametricPlot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{"1", 
        RowBox[{"Cos", "[", "t", "]"}]}], ",", 
       RowBox[{
        RowBox[{"1", "/", "5"}], " ", 
        RowBox[{"Sin", "[", "t", "]"}], 
        RowBox[{"(", 
         RowBox[{"1", "+", 
          RowBox[{"2", 
           SuperscriptBox[
            RowBox[{"(", 
             FractionBox[
              RowBox[{
               RowBox[{"Cos", "[", 
                RowBox[{"t", "/", "2"}], "]"}], "+", 
               RowBox[{"Sin", "[", 
                RowBox[{"t", "/", "2"}], "]"}]}], 
              SqrtBox["2"]], ")"}], "150"]}]}], ")"}]}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "0", ",", 
       RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"ParametricPlot", "[", 
    RowBox[{
     RowBox[{"{", 
      RowBox[{
       RowBox[{
        RowBox[{"1", 
         RowBox[{"Cos", "[", "t", "]"}]}], "-", 
        RowBox[{"5", 
         SuperscriptBox[
          RowBox[{"Cos", "[", 
           RowBox[{"2", "t"}], "]"}], "5"]}]}], ",", 
       RowBox[{
        RowBox[{
         RowBox[{"1", "/", "3"}], " ", 
         RowBox[{"Sin", "[", "t", "]"}]}], "+", 
        SuperscriptBox[
         RowBox[{"Sin", "[", 
          RowBox[{"t", "/", "2"}], "]"}], "5"]}]}], "}"}], ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "0", ",", 
       RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], 
   "\[IndentingNewLine]"}]}]], "Input",
 CellChangeTimes->CompressedData["
1:eJwdxW0o43EAB/A/ceMMY1pJcc6Uk3QN6Sxsd+K6N0wR5Wbc7l5cntsr52ls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  "]],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw123c4lf//OHCrjFAJSaQlqaS3lkTPooWiQhQtZWREVGahCJGUJNnZM3vz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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJxTTMoPSmViYGAwAWIQDQPGYPB4//mKBT1TJq23R+Xvh/NPL5vd4Fh8Ac5n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     "]]}, 
   {Hue[0.1421359549995791, 0.6, 0.6], LineBox[CompressedData["
1:eJxTTMoPSmViYGAwAWIQDQPGYPDZ/nzFgp4pk9bbo/L3w/mnl81ucCy+AOcz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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  ImageSize->{Automatic, 160.00531387262856`},
  Method->{},
  PlotRange->{{-1.799999789643311, 6.283185307179586}, {-0.6, 1.2}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.612112837011739*^9, 3.612112910323764*^9}, {
   3.6121129445203333`*^9, 3.6121130185483837`*^9}, {3.6121135425216703`*^9, 
   3.612113550331285*^9}, {3.6121160964470463`*^9, 3.612116171391831*^9}, 
   3.612116331911079*^9, {3.612153581334284*^9, 3.612153604135126*^9}, {
   3.612153819382457*^9, 3.612153833211664*^9}, {3.612153875295087*^9, 
   3.612153896954879*^9}, 3.6121539615291653`*^9, {3.612153998590653*^9, 
   3.612154016597904*^9}, 3.612154279873603*^9, {3.6125794987441187`*^9, 
   3.612579592574751*^9}, {3.612644474509268*^9, 3.612644511525407*^9}, {
   3.612655716956994*^9, 3.6126557634541893`*^9}, 3.612657764403133*^9, {
   3.612658078773348*^9, 3.612658140854375*^9}, 3.612906849334751*^9, {
   3.612906894505583*^9, 3.612906913458692*^9}, 3.6129070475563183`*^9, {
   3.612907141182825*^9, 3.6129071768584967`*^9}, {3.612907258839135*^9, 
   3.612907284881976*^9}, {3.612907389835826*^9, 3.612907399183888*^9}, 
   3.6129074618566027`*^9, {3.612907575668688*^9, 3.612907654145362*^9}, 
   3.612908057602592*^9, 3.612908095508459*^9, {3.612908169246683*^9, 
   3.612908210536352*^9}, {3.612908532821721*^9, 3.6129085883420773`*^9}, {
   3.612908647641308*^9, 3.6129086892717247`*^9}, 3.6129087450458508`*^9, {
   3.612990220586537*^9, 3.612990312061048*^9}, {3.61343913641323*^9, 
   3.613439209307826*^9}, {3.613439277660572*^9, 3.6134393016149797`*^9}, 
   3.613492205923419*^9, {3.613492256420475*^9, 3.6134922615292063`*^9}, 
   3.613851595113604*^9, {3.613851741155864*^9, 3.613851773228745*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw123c8lf/7OHCj3ikkoz2opGQklVLqQkokq6EhKsnMHmVlJBKRvSNbZO9x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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  ImageSize->{Automatic, 160.00531387262856`},
  Method->{},
  PlotRange->{{-0.9999998831351729, 1.}, {-0.19999997185624097`, 
   0.5999981010863551}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.612112837011739*^9, 3.612112910323764*^9}, {
   3.6121129445203333`*^9, 3.6121130185483837`*^9}, {3.6121135425216703`*^9, 
   3.612113550331285*^9}, {3.6121160964470463`*^9, 3.612116171391831*^9}, 
   3.612116331911079*^9, {3.612153581334284*^9, 3.612153604135126*^9}, {
   3.612153819382457*^9, 3.612153833211664*^9}, {3.612153875295087*^9, 
   3.612153896954879*^9}, 3.6121539615291653`*^9, {3.612153998590653*^9, 
   3.612154016597904*^9}, 3.612154279873603*^9, {3.6125794987441187`*^9, 
   3.612579592574751*^9}, {3.612644474509268*^9, 3.612644511525407*^9}, {
   3.612655716956994*^9, 3.6126557634541893`*^9}, 3.612657764403133*^9, {
   3.612658078773348*^9, 3.612658140854375*^9}, 3.612906849334751*^9, {
   3.612906894505583*^9, 3.612906913458692*^9}, 3.6129070475563183`*^9, {
   3.612907141182825*^9, 3.6129071768584967`*^9}, {3.612907258839135*^9, 
   3.612907284881976*^9}, {3.612907389835826*^9, 3.612907399183888*^9}, 
   3.6129074618566027`*^9, {3.612907575668688*^9, 3.612907654145362*^9}, 
   3.612908057602592*^9, 3.612908095508459*^9, {3.612908169246683*^9, 
   3.612908210536352*^9}, {3.612908532821721*^9, 3.6129085883420773`*^9}, {
   3.612908647641308*^9, 3.6129086892717247`*^9}, 3.6129087450458508`*^9, {
   3.612990220586537*^9, 3.612990312061048*^9}, {3.61343913641323*^9, 
   3.613439209307826*^9}, {3.613439277660572*^9, 3.6134393016149797`*^9}, 
   3.613492205923419*^9, {3.613492256420475*^9, 3.6134922615292063`*^9}, 
   3.613851595113604*^9, {3.613851741155864*^9, 3.6138517732987947`*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw0m3k4lP/3/+0i+2BokUhEREqSnDtRkiyhEpWULBEJlUKW3igpS5Ks2UpS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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  ImageSize->{558.418561120013, Automatic},
  Method->{},
  PlotRange->{{-5.999988196664069, 5.005000774377413}, {-0.25809666980119983`,
    1.0442412266761183`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.612112837011739*^9, 3.612112910323764*^9}, {
   3.6121129445203333`*^9, 3.6121130185483837`*^9}, {3.6121135425216703`*^9, 
   3.612113550331285*^9}, {3.6121160964470463`*^9, 3.612116171391831*^9}, 
   3.612116331911079*^9, {3.612153581334284*^9, 3.612153604135126*^9}, {
   3.612153819382457*^9, 3.612153833211664*^9}, {3.612153875295087*^9, 
   3.612153896954879*^9}, 3.6121539615291653`*^9, {3.612153998590653*^9, 
   3.612154016597904*^9}, 3.612154279873603*^9, {3.6125794987441187`*^9, 
   3.612579592574751*^9}, {3.612644474509268*^9, 3.612644511525407*^9}, {
   3.612655716956994*^9, 3.6126557634541893`*^9}, 3.612657764403133*^9, {
   3.612658078773348*^9, 3.612658140854375*^9}, 3.612906849334751*^9, {
   3.612906894505583*^9, 3.612906913458692*^9}, 3.6129070475563183`*^9, {
   3.612907141182825*^9, 3.6129071768584967`*^9}, {3.612907258839135*^9, 
   3.612907284881976*^9}, {3.612907389835826*^9, 3.612907399183888*^9}, 
   3.6129074618566027`*^9, {3.612907575668688*^9, 3.612907654145362*^9}, 
   3.612908057602592*^9, 3.612908095508459*^9, {3.612908169246683*^9, 
   3.612908210536352*^9}, {3.612908532821721*^9, 3.6129085883420773`*^9}, {
   3.612908647641308*^9, 3.6129086892717247`*^9}, 3.6129087450458508`*^9, {
   3.612990220586537*^9, 3.612990312061048*^9}, {3.61343913641323*^9, 
   3.613439209307826*^9}, {3.613439277660572*^9, 3.6134393016149797`*^9}, 
   3.613492205923419*^9, {3.613492256420475*^9, 3.6134922615292063`*^9}, 
   3.613851595113604*^9, {3.613851741155864*^9, 3.6138517733136053`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"Cos", "[", "t", "]"}], "+", 
      RowBox[{"0.8", 
       RowBox[{"Cos", "[", 
        RowBox[{"5", "t"}], "]"}]}]}], ",", 
     RowBox[{
      RowBox[{"Sin", "[", "t", "]"}], "+", 
      RowBox[{"0.08", 
       RowBox[{"Sin", "[", 
        RowBox[{"5", "t"}], "]"}]}]}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.613358351104083*^9, 3.613358351734117*^9}, {
  3.613358988446557*^9, 3.6133591699787703`*^9}, {3.613359745549362*^9, 
  3.613359829687661*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwsmXk4ld8TwEWiqCR7oSRJQgsJNYoklShKkpRSVAgVpaKUQojsS2StiOz7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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-1.799997545839723, 1.8}, {-1.0799995778437725`, 
   1.0799996348235843`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.613359075851452*^9, 3.613359090323077*^9}, {
  3.613359124999251*^9, 3.613359170826304*^9}, {3.6133597817265463`*^9, 
  3.613359830421323*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"RegionPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{
     RowBox[{
      SqrtBox[
       RowBox[{
        SuperscriptBox[
         RowBox[{"(", 
          RowBox[{"x", "-", 
           SubscriptBox["x", "0"]}], ")"}], "2"], "+", 
        SuperscriptBox[
         RowBox[{"(", 
          RowBox[{"y", "-", 
           SubscriptBox["y", "0"]}], ")"}], "2"]}]], "-", 
      RowBox[{"(", 
       RowBox[{
        SubscriptBox["r", "0"], "+", 
        RowBox[{"\[Epsilon]", " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"2", 
           RowBox[{"Arg", "[", 
            RowBox[{
             RowBox[{"(", 
              RowBox[{"x", "-", 
               SubscriptBox["x", "0"]}], ")"}], "+", 
             RowBox[{"\[ImaginaryI]", " ", 
              RowBox[{"(", 
               RowBox[{"y", "-", 
                SubscriptBox["y", "0"]}], ")"}]}]}], "]"}]}], "]"}]}]}], 
       ")"}]}], ">", "0"}], "/.", 
    RowBox[{"{", 
     RowBox[{
      RowBox[{
       SubscriptBox["x", "0"], "\[Rule]", "0.5"}], ",", 
      RowBox[{
       SubscriptBox["y", "0"], "\[Rule]", "0.5"}], ",", 
      RowBox[{"\[Epsilon]", "\[Rule]", "0.05"}], ",", 
      RowBox[{
       SubscriptBox["r", "0"], "\[Rule]", "0.25"}]}], "}"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "0", ",", "1"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", "0", ",", "1"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.612909428209845*^9, 3.612909432849162*^9}, {
  3.613358124409034*^9, 3.613358309446501*^9}, {3.613358420817401*^9, 
  3.613358497048028*^9}, {3.613358528199861*^9, 3.613358541306138*^9}, {
  3.613358584101983*^9, 3.6133586236782637`*^9}, {3.613359375289771*^9, 
  3.613359491905409*^9}, {3.613359551606392*^9, 3.6133595671561728`*^9}, {
  3.61335972497332*^9, 3.613359731681408*^9}, {3.6133598558336782`*^9, 
  3.613360051664301*^9}}],

Cell[BoxData[
 GraphicsBox[GraphicsComplexBox[CompressedData["
1:eJx1mHt0U1UWh0sFBBdlBBRsCgooGsEpCKQjDz3VKMWBKSkWnxiZ8qqmPETG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   "], {{
     {RGBColor[0.798413061722744, 0.824719615472648, 0.968322270542458], 
      EdgeForm[None], GraphicsGroupBox[{PolygonBox[CompressedData["
1:eJxFmgn811PWx3/3axnLMBkUEm0ULQqVSaEGiVL2auzJ0pTshJQoZUtZIlIZ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         "]], PolygonBox[CompressedData["
1:eJwtlfdvj1EUxr/32HuG2HvFij0j9ipFlbZo0dqtTat21SwSIkZTIgQxY8Ze
EfGb/0BEYguakNjr8zjvD5/c53zf+9733nOfc75N0hcmLLBYLDYXSsIQgtch
FsuC9TCY+AXjPFgLy4mXQjL6IgxAN4bp6FxIQ0+Fw+hM1luBrgkpxFdgCvoX
49HgcwqJx8Mu9CN4BWOJCzSf9/uj60EacQ5MQj9lTOHZQcYfMJnfJjMOh0ro
LDiPfsyckeiqkBR8D9PR02Alz44Qf4bnMAe2wBeoxfNJjAcgXcmBE+hjMAo9
2nxuPMxGz4Uz2nfws6War60zjkHHw7bgZ0pAj4Md6J2Qr7XgDnoWJJnvQd/e
D89gO789CL7ndzon8UbGRfA32qP2dhwMPQNOok/BQrQuWLlQjhuZv6O506Ak
cWu9g14NAd0M0vU9GIhuARnoVcHXLgGng3+jOXqm+bduQR30d8ZDwe8khfhb
8Lsqgt7EvWBY8Bx3RleEfO0VuqKrwCb0YuUEXco81zOhDLqtco4+C93R++Bh
8Dv+ACOINzMugQr6lnKAToQ3MJR4A+P84F5KJi6MPLUW/Ql9HW7ARHMPy7t7
YQ06ztxrmrNKXjL3+lXin6ob4puM2cH39pHxScz3OEh3B7e1lnyH3gp3g3uo
AN0T7qPvwQR5x1zvifb+NsqVzpBoXkOqnd2Qh14HqcH30M/8TDrLcp3ZPCfK
xQXIML9D3Z08vgi92Hwt7VneVc6Va3m4GJaZ1/7S4F4uB+eCe1q1V9l8bdXg
JnOPy9u3Iy//YYwL7ukexNXhktaFTPMeoNrXmtWIs82fqedornKiXOidGuZ3
pLu5HNw73czvXh6qb34nugv1ENW6epp6mWq+Hbqscha8x6m23kfeU419jWpS
tVgYeas4Ors8prvKMf+27uw3NCSeyrgCXgbvqeqlmcFrQzVRFNVIH3Rf81pU
TlQbq+Fa8BrpgC4PecF7srwiD8k78kwr8xr9X5tQG51r7kWtoXc7mntda6jW
upj3DtWcarmNeW2pppWL9uZ7/Z8TdGnz3qaaa2J+Rp1NPb+lec9Qr1CP2Gze
U9RL1NPqmntQ3pMnm5r/Z+i/Qj2mgXmPV29XzjqZ90j1RtXsPzi4xr8=
         "]]}]}, {},
      {}, {}, {}}, 
    {GrayLevel[0], Opacity[0.4], LineBox[CompressedData["
1:eJwt0DtOQgEUBNCHgOITP6C0EDttFZE/KkpHoi7BQIsNbEB6rbWVFmvocQOy
A9iDtB4Si5NMdSdzj5+eH3uRIAjabLDOGU6p8UCXAUPe+GDEF1O+mbNkxY4j
Oc7Jc0GBS4qUKFOhSo06Da645oYmt9zR4owsIb96FvwwY8KYT9555YU+He6p
csIRh6RJccA+e+ySXG8gZJsEW2wSJ0b0/19/cb0Zpg==
      "]], 
     LineBox[CompressedData["
1:eJwl0/dXT3EYwPHbNyshRDKTmS2ERCR7RfZKyh4lIxWSvRKyEgp/jD/DyM5K
RrJf5/jhdd7PfT73c8795cbn5GfmhQVB8JBuoSAo5hAlTOGxwyzdwDp+eV6v
G8nmOFN5Yn9B/2iKTuapuVzj+GvO0YBcBrCZEJsIZwgXqfPuFm3JAhby2e4Z
M8zPtUKH04YRXOKF/Ux9pZd1JG0ZxRVe28/SN1qpY2jHWK5Sbz9H3+k1HUcU
SVznvf1c/aj79QD76EQhDfY3dQKdWc45zjORg0SzgiK6UMUn9+ZpR8Zzgw92
X9lr3kMBy7jFUvLJ4613vtDevIsO7CaS2YymhkQyWUIEO3np3mLNYBGtGcZd
hrKDVmxlO9s4SzonOcUJznCaFiRwh8FMZyAPGEQY/blNP9Loy33i+e17+mg1
vZlGT+7Ri5/Oy/QYR+lBKqU0Ojui8/lhXqux1NKdZrvV+l3X6CNdpU26Ur9p
jHZlEskcDv3/J/4BfElXOw==
      "]]}}],
  AspectRatio->1,
  Frame->True,
  Method->{"TransparentPolygonMesh" -> True, "AxesInFront" -> True},
  PlotRange->{{0, 1}, {0, 1}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.6133586049782267`*^9, 3.613358624825781*^9}, {
  3.613359383102722*^9, 3.613359492936274*^9}, {3.613359554981504*^9, 
  3.613359568684423*^9}, {3.613359725957741*^9, 3.613359732289156*^9}, {
  3.613359857209269*^9, 3.613359896153796*^9}, {3.613359927654656*^9, 
  3.6133600523391027`*^9}}]
}, Open  ]],

Cell[BoxData["5"], "Input",
 CellChangeTimes->{3.613360039724701*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"Cos", "[", "t", "]"}], "+", 
   RowBox[{"Cos", "[", 
    RowBox[{"4", " ", "t"}], "]"}]}], "//", "FullSimplify"}]], "Input",
 CellChangeTimes->{{3.613359195337369*^9, 3.613359206246245*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Cos", "[", "t", "]"}], "+", 
  RowBox[{"Cos", "[", 
   RowBox[{"4", " ", "t"}], "]"}]}]], "Output",
 CellChangeTimes->{{3.613359198164713*^9, 3.613359206978525*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    FractionBox["1", "6"], 
    RowBox[{"{", " ", 
     RowBox[{
      RowBox[{
       RowBox[{"7", 
        RowBox[{"Cos", "[", "t", "]"}]}], "+", 
       RowBox[{"Sin", "[", 
        RowBox[{"4", "t"}], "]"}]}], ",", 
      RowBox[{
       RowBox[{"7", 
        RowBox[{"Sin", "[", "t", "]"}]}], "+", 
       RowBox[{"Cos", "[", 
        RowBox[{"4", "t"}], "]"}]}]}], "}"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.612908754374434*^9, 3.6129087785132513`*^9}, {
   3.612908935333124*^9, 3.612908940955882*^9}, 3.612908981446826*^9, {
   3.6129090194786377`*^9, 3.612909125292615*^9}, {3.612909230493771*^9, 
   3.612909299600943*^9}, {3.612909408121468*^9, 3.612909464501739*^9}, {
   3.6129095275551987`*^9, 3.6129095483622293`*^9}, {3.612909668404517*^9, 
   3.612909733092472*^9}, {3.612909826303074*^9, 3.6129099077692137`*^9}, {
   3.6129099792116747`*^9, 3.61291008093029*^9}, {3.6129107786266937`*^9, 
   3.6129108508534393`*^9}, {3.6129110984533567`*^9, 3.612911255423295*^9}, {
   3.612911887387549*^9, 3.6129119872854223`*^9}, {3.612912477716289*^9, 
   3.612912572754417*^9}, {3.612915435066185*^9, 3.6129154512116833`*^9}, {
   3.612915483648877*^9, 3.6129154947585897`*^9}, {3.612915603525466*^9, 
   3.612915632232785*^9}, {3.612915667317181*^9, 3.6129159925843067`*^9}, {
   3.61291602409588*^9, 3.6129161183226643`*^9}, 3.61291635488396*^9, {
   3.612917707188038*^9, 3.6129177183838*^9}, {3.612917904070202*^9, 
   3.612917906689196*^9}, {3.612972536793097*^9, 3.61297254849999*^9}, {
   3.613357931422023*^9, 3.613358121203618*^9}, 3.6133590636124783`*^9, {
   3.613359577171994*^9, 3.613359713574443*^9}, {3.613360065283318*^9, 
   3.613360334089693*^9}, {3.614660992539145*^9, 3.614661010965189*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw1m3c41e8f/xFKJZJCRUpFJckoCS+RIntVRqVBVoWKFIqyCpUKUbIrIxIp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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-1.2713936401731032`, 
   1.2713936110208224`}, {-1.0937039186605544`, 1.3333328667189717`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.612908750906103*^9, 3.6129087790553303`*^9}, 
   3.6129089420636*^9, 3.612908981876707*^9, {3.6129090201887903`*^9, 
   3.612909126213231*^9}, 3.612909237317985*^9, {3.612909273062902*^9, 
   3.6129093000572557`*^9}, 3.6129094668252497`*^9, {3.612909502251713*^9, 
   3.6129095502024517`*^9}, {3.6129096696700287`*^9, 3.612909733525194*^9}, {
   3.6129098363880997`*^9, 3.6129099082073603`*^9}, {3.612909989207546*^9, 
   3.612910081858759*^9}, {3.6129111134740877`*^9, 3.612911168407981*^9}, {
   3.61291121795996*^9, 3.612911255874927*^9}, {3.612911898677229*^9, 
   3.6129119878026543`*^9}, {3.612912547805264*^9, 3.612912573480851*^9}, 
   3.612915451807119*^9, 3.612915495739153*^9, {3.612915605597527*^9, 
   3.612915632742475*^9}, {3.612915670518083*^9, 3.6129159934698763`*^9}, {
   3.612916027952235*^9, 3.612916118744025*^9}, 3.6129163558606663`*^9, {
   3.612917711442411*^9, 3.612917719479871*^9}, 3.612917908660963*^9, {
   3.61297253957576*^9, 3.612972549977854*^9}, {3.6133579535247097`*^9, 
   3.613357962154458*^9}, {3.6133580063617687`*^9, 3.613358105408636*^9}, {
   3.613359584646744*^9, 3.613359714286399*^9}, {3.613360067398715*^9, 
   3.613360334990741*^9}, 
   3.61466101509206*^9},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[BoxData["7"], "Input",
 CellChangeTimes->{3.613360160386999*^9}],

Cell[BoxData["3"], "Input",
 CellChangeTimes->{3.613360081362911*^9}],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.613359672197751*^9, 3.613359673825498*^9}}],

Cell[BoxData[{
 RowBox[{"fx", "=", 
  RowBox[{"cos", 
   RowBox[{"(", "u", ")"}], "*", 
   RowBox[{
    RowBox[{"(", 
     RowBox[{
      RowBox[{"abs", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"cos", 
          RowBox[{"(", 
           RowBox[{"1", "*", 
            RowBox[{"u", "/", "4"}]}], ")"}]}], ")"}], "^", "0.5"}]}], "+", 
      RowBox[{"abs", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"sin", 
          RowBox[{"(", 
           RowBox[{"1", "*", 
            RowBox[{"u", "/", "4"}]}], ")"}]}], ")"}], "^", "0.5"}]}]}], 
     ")"}], "^", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"-", "1"}], "/", "0.3"}], ")"}]}]}]}], "\n", 
 RowBox[{"fy", "=", 
  RowBox[{"cos", 
   RowBox[{"(", "u", ")"}], "*", "sin", 
   RowBox[{"(", "v", ")"}], "*", 
   RowBox[{
    RowBox[{"(", 
     RowBox[{
      RowBox[{"abs", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"cos", 
          RowBox[{"(", 
           RowBox[{"1", "*", 
            RowBox[{"u", "/", "4"}]}], ")"}]}], ")"}], "^", "0.5"}]}], "+", 
      RowBox[{"abs", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"sin", 
          RowBox[{"(", 
           RowBox[{"1", "*", 
            RowBox[{"u", "/", "4"}]}], ")"}]}], ")"}], "^", "0.5"}]}]}], 
     ")"}], "^", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"-", "1"}], "/", "0.3"}], ")"}]}], "*", 
   RowBox[{
    RowBox[{"(", 
     RowBox[{
      RowBox[{"abs", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"cos", 
          RowBox[{"(", 
           RowBox[{"5", "*", 
            RowBox[{"v", "/", "4"}]}], ")"}]}], ")"}], "^", "1.7"}]}], "+", 
      RowBox[{"abs", 
       RowBox[{
        RowBox[{"(", 
         RowBox[{"sin", 
          RowBox[{"(", 
           RowBox[{"5", "*", 
            RowBox[{"v", "/", "4"}]}], ")"}]}], ")"}], "^", "1.7"}]}]}], 
     ")"}], "^", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"-", "1"}], "/", "0.1"}], ")"}]}]}]}]}], "Input",
 CellChangeTimes->{{3.6129106366474123`*^9, 3.6129106455450487`*^9}, 
   3.612910707079327*^9, {3.612910762416901*^9, 3.612910768471517*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{"Cos", "[", "t", "]"}], ",", 
      RowBox[{
       RowBox[{"1", "/", "15"}], " ", 
       RowBox[{"Sin", "[", "t", "]"}]}]}], "}"}], 
    RowBox[{"(", 
     RowBox[{"1", "+", 
      RowBox[{"5", 
       SuperscriptBox[
        RowBox[{"(", 
         FractionBox[
          RowBox[{
           RowBox[{"Cos", "[", 
            RowBox[{"t", "/", "2"}], "]"}], "+", 
           RowBox[{"Sin", "[", 
            RowBox[{"t", "/", "2"}], "]"}]}], 
          SqrtBox["2"]], ")"}], "500"]}]}], ")"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{"Cos", "[", "t", "]"}], ",", 
      RowBox[{
       RowBox[{"1", "/", "5"}], " ", 
       RowBox[{"Sin", "[", "t", "]"}]}]}], "}"}], 
    RowBox[{"(", 
     RowBox[{"1", "+", 
      RowBox[{"1.1", 
       RowBox[{"(", 
        FractionBox["1", 
         RowBox[{
          SuperscriptBox["\[ExponentialE]", 
           RowBox[{"100", 
            RowBox[{"(", 
             RowBox[{"t", "-", "\[Pi]"}], ")"}]}]], "+", "1"}]], ")"}], 
       SuperscriptBox[
        RowBox[{"Sin", "[", "t", "]"}], "200"]}]}], ")"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{"Cos", "[", "t", "]"}], ",", 
      RowBox[{
       RowBox[{"1", "/", "5"}], " ", 
       RowBox[{"Sin", "[", "t", "]"}]}]}], "}"}], 
    RowBox[{"(", 
     RowBox[{"1", "+", 
      RowBox[{"0.6", 
       RowBox[{"(", 
        RowBox[{"1", "-", 
         RowBox[{"Tanh", "[", 
          RowBox[{"100", 
           RowBox[{"(", 
            RowBox[{"t", "-", "\[Pi]"}], ")"}]}], "]"}]}], ")"}], 
       SuperscriptBox[
        RowBox[{"Sin", "[", "t", "]"}], "200"]}]}], ")"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{"Cos", "[", "t", "]"}], ",", 
      RowBox[{
       RowBox[{"1", "/", "5"}], " ", 
       RowBox[{"Sin", "[", "t", "]"}]}]}], "}"}], 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"2", 
       RowBox[{"(", 
        RowBox[{"1", "-", 
         RowBox[{"Tanh", "[", 
          RowBox[{"100", 
           RowBox[{"(", 
            RowBox[{"t", "-", "\[Pi]"}], ")"}]}], "]"}]}], ")"}]}], "+", 
      RowBox[{"1.1", 
       SuperscriptBox[
        RowBox[{"Sin", "[", "t", "]"}], "200"]}]}], ")"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     FractionBox["1", 
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"100", 
         RowBox[{"(", 
          RowBox[{"t", "-", "\[Pi]"}], ")"}]}]], "+", "1"}]], ",", 
     RowBox[{
      RowBox[{"1", "/", "2"}], "-", 
      RowBox[{
       RowBox[{"1", "/", "2"}], 
       RowBox[{"Tanh", "[", 
        RowBox[{"100", 
         RowBox[{"(", 
          RowBox[{"t", "-", "\[Pi]"}], ")"}]}], "]"}]}]}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.6111619818678637`*^9, 3.611162145099712*^9}, {
   3.611162199387154*^9, 3.611162238067812*^9}, {3.611162771963526*^9, 
   3.611162793983696*^9}, {3.611162890057639*^9, 3.611163157504365*^9}, {
   3.6111632002239647`*^9, 3.611163288458066*^9}, {3.611163383066094*^9, 
   3.6111634192982807`*^9}, {3.611163543114402*^9, 3.6111636887063313`*^9}, {
   3.611163729028234*^9, 3.611163746371627*^9}, {3.611163780642498*^9, 
   3.611163849423457*^9}, {3.6111638995435047`*^9, 3.611163947093351*^9}, {
   3.611164201168397*^9, 3.61116424572228*^9}, {3.611164301978292*^9, 
   3.611164305166548*^9}, {3.6111643728043613`*^9, 3.6111644900599413`*^9}, {
   3.6111645210230093`*^9, 3.611164542301752*^9}, {3.6111645895436697`*^9, 
   3.611164643722413*^9}, {3.611164791522277*^9, 3.6111650360560427`*^9}, {
   3.611165069607153*^9, 3.611165077159213*^9}, {3.611165196666684*^9, 
   3.611165237691121*^9}, {3.6113744753055468`*^9, 3.6113745534288692`*^9}, {
   3.611414892692409*^9, 3.611414918723256*^9}, {3.612096745857193*^9, 
   3.6120967671519537`*^9}, {3.61209687685456*^9, 3.612097014521606*^9}, {
   3.612097046259347*^9, 3.612097111214589*^9}, {3.612108561819996*^9, 
   3.612108563600762*^9}, {3.6121086021728487`*^9, 3.612108704319491*^9}, {
   3.612108735506713*^9, 3.612108759749332*^9}, {3.61210884034866*^9, 
   3.6121088985026503`*^9}, {3.61210938956621*^9, 3.612109492475872*^9}, {
   3.6121096710199127`*^9, 3.6121097011101713`*^9}, {3.6121097428568497`*^9, 
   3.612109781173585*^9}, {3.612110074236103*^9, 3.612110103114341*^9}, {
   3.6121101486359787`*^9, 3.612110161030238*^9}, {3.6121102082587423`*^9, 
   3.612110224330474*^9}, {3.61211028259986*^9, 3.612110483874971*^9}, {
   3.612110626860814*^9, 3.612110800715803*^9}, {3.612111032631531*^9, 
   3.612111131181156*^9}, {3.612112058037417*^9, 3.612112058139248*^9}, 
   3.6121123670430403`*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw13GVUVc3XAHBRVAxUBEXFQFQsWsrALQIiJaFYoIiIUiIh8iAtKd3SUtJx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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-0.9999998831351729, 1.}, {-0.06666665728541364, 
   0.2279950421260808}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.6121101368074427`*^9, 3.6121101616491823`*^9}, {
   3.612110212103937*^9, 3.612110224845427*^9}, {3.6121102833467484`*^9, 
   3.6121104845301437`*^9}, {3.612110631861739*^9, 3.612110801495316*^9}, {
   3.612111035166675*^9, 3.612111132368442*^9}, 
   3.612112058836582*^9},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw123c4Vm/4AHCUIqSQ0pBvQ2QUoqXuSEQSGlSikrKy9ypKZGRlRpQtZe9x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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-0.9999998831351729, 1.}, {-0.19999997185624097`, 
   0.41999459301830167`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.6121101368074427`*^9, 3.6121101616491823`*^9}, {
   3.612110212103937*^9, 3.612110224845427*^9}, {3.6121102833467484`*^9, 
   3.6121104845301437`*^9}, {3.612110631861739*^9, 3.612110801495316*^9}, {
   3.612111035166675*^9, 3.612111132368442*^9}, 
   3.612112058909005*^9},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw123lcjF/UAHBFKspSiaSkkmhBKT/EIVGRtEghWUMLLbK1IVIi7av2vUT7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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-0.9999998831351729, 1.}, {-0.19999997185624097`, 
   0.439994103687702}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.6121101368074427`*^9, 3.6121101616491823`*^9}, {
   3.612110212103937*^9, 3.612110224845427*^9}, {3.6121102833467484`*^9, 
   3.6121104845301437`*^9}, {3.612110631861739*^9, 3.612110801495316*^9}, {
   3.612111035166675*^9, 3.612111132368442*^9}, 3.612112058923596*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJzFm+VbVU/U9+mGo6SCCIoBIigYKCrrCEhKGT9CFANUQEFKSUFCkBaQ7hZQ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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-3.9955643896100494`, 4.}, {-0.21999377750243518`, 
   1.0199945199829947`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.6121101368074427`*^9, 3.6121101616491823`*^9}, {
   3.612110212103937*^9, 3.612110224845427*^9}, {3.6121102833467484`*^9, 
   3.6121104845301437`*^9}, {3.612110631861739*^9, 3.612110801495316*^9}, {
   3.612111035166675*^9, 3.612111132368442*^9}, 3.612112058935454*^9}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw91mk0Ve/bB3BRzh6QeShDOZIoIVM5e++LqKgkQiVjEkohyViRIVFJRSRU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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJxF1nk4VVsfB/BjuOzDTaYM99Ap4UqlLtHg7L0Xr0r0KhT3Zp5KQofcblKK
EJmHXJ1MXTIlEjJEqGTMdSNcIp1XInJMiWN69zmOvdfz7Gc9n+f7W+uP9dvr
edZWxwtmLvwkEmkA+zizQI1I2/+0AxASd0yiZu7yvUlxhei6Y6etixPjanDr
1huJ6F9sx02/YuJQTO/B7VHuEsW/bRB358hRcrbjEO7bu+dIT38bwe21o/FO
7YNx3Gyn8wX9npO4HastTsScmcbtNNVZWxs6iztiT9mFrJA53Py1ZfuCrszj
llA3bvuQxMZtmKafMRm3hFuW1Xr4etkKbkZDJZ/AORJYN01Rb3WLMx/uHYPi
Q9d8+HE/ypF0LfUWwH11wKZjR4ggbi/afuPUhB9ws9MMHMdihHC30xn2f/wl
jNvtzJKwKVMYCK1yBgsVtLYtVFeCgI/YCtf/WGy8KasPAU+ZTq5TTWstBB0h
4N9NXeJ4nq4zxXcGAnShI2yOzWLyw1fPQaCTGfGd4/xCJdVlDwh0iYbMcPzD
30m1bC8IVMzGf+XYdkLMav53CEgEtg5xXL4h+Ns3XwgMCXd1cyy5azF65hoE
5KhPXnHsfsxLfSoAAqnKF3I4fn3+86uJYAiEHC/x55gabmM3HgaB92Eyehxf
zutYGI2EgFcFZXgF89umowmfYyGwg1Fvx/HO0RqNT3cgwK53u7uMOQTSaWLe
hcCxXWE+S5gHf853GkyBwI9M6VdszAeOKK3034eAke/tQ/OY92Y0hzY8gEBQ
9kL+LGaNVW+polwIZGpLu7Iwq1lRUhmPIODdGlX4GbNS2Uu1oCIIZPc7273H
rCDlXuxRCgGzldKWFswyF6QRywoIOOTHBxRjFm+pagTVELjU4f4lGrPozy7m
6nUQUNP2emWFWejmhgGpemz/Y7NWGzGTPpS6LjdCwLrpnmvaCgtlH7SdGW6F
wHfZx06Lyyx0NlHIv70dAhFSZvKimCemC6DKTgiEBbHlHy6y0BETy/iMHqzf
r1+EZi+wUGbeqmLkewgkK1wJLZljof1COTmXBrHzeDmm4zTNQnscT2jZD2H9
o2oWS4xj5/t8vvroCARkvy5IdDJZaOtP9w21xrH/5bqCrfk7rF+XjnYoTEIg
3a9xMLWOhda+nbIRmoVAHuOwwlgmC63UYIywvkPA1lC04IAfCy25rX/x30UI
0P4lDQ0jLLRw+Mvyi1UIKA6gD6gjE2iefnxovgAZnL71rfSE+wSamaorlShM
Bl6HZvKqq7+iqez/pVwXJQNbF7GstJZxNMkiQu3cRjJQK6JUut8cQ+Oe7C02
kyIDStTmkxKdo2iEWD9MkyWD5MLdxXHFn9EQt+BGFQoZiJRL5umrfkIDXu8y
30jF6q9/5Pc2YKJXlbr655XIQD9wWEjNZwC95O/vylQlA2j8u2u0Xw9K71Wd
aVEng5ciDrQXgh2om87f10o1yKBtFkruyW1FneP+gNI0yWB479QCZWM9dh+o
8aE6ZDBr0KLOd/I5+qtRo6L3QTLYwj92qzSgFDXPoudYIWRAb9a9Uq9WgJrw
y2sd0icD1+4aSvBCJmpoW1etcZgMBtsUXW/ypaD6lecM5YzIoBYeU05YiEdp
MpIdfCbYfnp3zm66EI7qeFfajJmSASlGt9vtTSC6p81xpPMUZu23VXLVvqi6
uujF579htr9dWnfXC1UJKV7OtiGDG7avra3FXNEtTKvQWAcsf6bH98zTHv0J
EZTyc8HcNK/i62WBSjPyU5zPYZ5U2O37wAQVmzupZuKBOU9zc8OYAQqZLT/Z
54XZOrg8M5qG8hc8gLf+jvlkJBTjr4UukU0aRXwxP06+Ypqsjn53mTObvYp5
ZF/E2e1K6HRdan//DcztlMf/bZZDxxWPuDYEYd7y4pjWmDg67MuafhyKuXb3
vg5ZYXTw3Z/XGBGYb0RmHgxeRXp/AVBQDGZAoU8FfkM6I0fiPBI4uUJ4mPVX
pG00RtEyiePE5gryENJ06EAOSMZM+s/uzN/6kMsN/hrX0zkWJQ1LvEXUjr4q
qc7kOFkvfLAB6W4m6y7lcOwcPxtRg4QcO1538BHHs/stekoQnbaEI75FHJ8o
NAp/iHw63vumrJRjuk2R5l9Iwj/Uk3MVHNfmDogmIQbmLr17n3MMnmq+jkZm
O/PsL77g2B79eSUIybCYHC56za3X16/2Q8x6tD0mmzkmGZeYeyP8p/1mNP7m
mnZtnyvypK/W16OD66J3q3aIg40QKb+b6xhd5VOI+AfjkC99XFvEs4yRWvvY
H7cPcs2Y9tFH6MyuuLNDXN9wc9qPUJ0V5LNGuHafVNiDtH1ySBsa57oxwUgF
8T+brbJtaq0eVVJANEbHHzp843qLR6Ik0u+mqZm+wLV9djSERIz/UT6wzHW6
+kESQvOsRhT5Rbjrtby+weMs/noroTUfOTUO3/MyNGaIrFm5nAkbzUT+0yPG
NWlvVQ/M9umwlJVaM8OyHc6dkxs4JbtmuaR6+NfLts4JlDXnh1bBEDvjy1sq
L+99Apf5jdIllNcsPpoDn1nW+H5cbc3g93RY5rrPtaidPNfcgetJlQJv9qzZ
vioC9glcDRPV5uVLgbCy4CFxowM8y/jCHcG3E0PhNZPi6XCgcLtCg96abwy7
wJphmzJ+OMzLp6xhpojVdgMjnqnmcGxEemGgCc8GR2EgNqxdZ8bzEwBPRu+o
WrXgWVwHTpfw0keseFbbBR+Pf9p41Y5nsA1ekV4yeebEM10eLkjUe7dwlud2
cdhW7pbVfvf1eiF4A6P14yX6updpVRTsveLD840ZmnuK5cTM5XWP0hSoKT6a
13gmfaS1pDPZ9IB1d9GuKKkFFAavu42mnukhPBG27le0XpXiyJ1R6y6nhWXP
S52PW/dj2v7tCCM3cd05tJG8m1tGGOtOp/25sylLNW3dMbTDBWK7XDIIPyi6
e4D5cN0kktuilXpPIeE9hzZT2ooJV/X8tVTxjHDH6sOa2BbCfCbPD+mNEbb5
wjRNVxfFvWnbTjfbXMJv+aBA+aofcZdCF7Pamzbg3rlJ3M2xXgw3K2pOWqtr
I+5tt27tvuAmjpt5uq9X/zNhw08dC6WeErgve7u4ynwlbPL0npHMJUncE0tu
VwXmCN/vDijxvCiFm+0K2/suElZcjrXyuiKNe/hIeDMkuAn3S9VWdHM4YTco
S3ArWQZ3Wboy/DKWcJsurd5MQhb3vNs9c/sowo0n0k5tkJHD7XiAlp2dQPjc
1zff3icSpt+3M5C8S/g6+ebHqymEk/9tophlEe7ytYxZKiNsVOnta9pH2NRT
sDGkn/CvSokyVR8In71dUaw6RDjoNGlicZzwc3akY9YK4foCalEfSR53q2PR
qrgA4b7mzmQ/YcLzDEr3CXHCqyaPVEIkCQsJoD7PpAlLn3eUUJUnTKHO2llR
CCt1BBfEKBJWvyW7XE8l/IturvHiVsL/B4Dv3l0=
     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->NCache[{{0, 2 Pi}, {0., 1.}}, {{0, 6.283185307179586}, {0., 1.}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.6121101368074427`*^9, 3.6121101616491823`*^9}, {
   3.612110212103937*^9, 3.612110224845427*^9}, {3.6121102833467484`*^9, 
   3.6121104845301437`*^9}, {3.612110631861739*^9, 3.612110801495316*^9}, {
   3.612111035166675*^9, 3.612111132368442*^9}, 3.612112058940027*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.6121101329624977`*^9, 3.612110132999083*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw123c4Vm/4AHCUIqSQ0pBvQ2QUoqXuSEQSGlSikrKy9ypKZGRlRpQtZe9x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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-0.9999998831351729, 1.}, {-0.19999997185624097`, 
   0.41999459301830167`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.611162022927827*^9, 3.611162035515938*^9}, {
   3.611162070881236*^9, 3.611162145513773*^9}, {3.611162203422757*^9, 
   3.6111622384974937`*^9}, {3.6111627729992447`*^9, 3.611162794728648*^9}, {
   3.611162891753628*^9, 3.61116315822429*^9}, {3.611163201300222*^9, 
   3.611163288876153*^9}, {3.6111633844233713`*^9, 3.611163419799666*^9}, {
   3.6111635474392347`*^9, 3.611163689239029*^9}, {3.611163730916421*^9, 
   3.611163747140781*^9}, {3.611163781173532*^9, 3.611163861388054*^9}, {
   3.611163900422316*^9, 3.611163947547069*^9}, {3.6111642298056602`*^9, 
   3.611164246930952*^9}, 3.611164307117742*^9, {3.611164382393544*^9, 
   3.6111644908724413`*^9}, {3.611164522629056*^9, 3.6111645429261913`*^9}, 
   3.611164590410926*^9, {3.6111646255338783`*^9, 3.6111646446054*^9}, {
   3.611164792403199*^9, 3.611164826251396*^9}, {3.6111648900778217`*^9, 
   3.61116496830731*^9}, {3.61116500175616*^9, 3.611165036542562*^9}, {
   3.61116507062253*^9, 3.611165077883089*^9}, {3.611165197079905*^9, 
   3.6111652386310997`*^9}, {3.611374477158511*^9, 3.611374554008848*^9}, {
   3.6114148937888317`*^9, 3.611414919109997*^9}, 3.612096768806164*^9, {
   3.612096892636816*^9, 3.61209701504067*^9}, {3.612097071831416*^9, 
   3.612097112082941*^9}, {3.612108608639592*^9, 3.612108633107952*^9}, {
   3.61210866315874*^9, 3.6121087053833103`*^9}, {3.61210873673517*^9, 
   3.612108761596652*^9}, {3.612108845039351*^9, 3.612108899383665*^9}, {
   3.612109390719858*^9, 3.612109493110351*^9}, {3.612109686502378*^9, 
   3.612109702002121*^9}, {3.612109745958332*^9, 3.612109782344554*^9}, {
   3.612110086199441*^9, 3.612110103704083*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw123lcjF/UAHBFKspSiaSkkmhBKT/EIVGRtEghWUMLLbK1IVIi7av2vUT7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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-0.9999998831351729, 1.}, {-0.19999997185624097`, 
   0.439994103687702}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.611162022927827*^9, 3.611162035515938*^9}, {
   3.611162070881236*^9, 3.611162145513773*^9}, {3.611162203422757*^9, 
   3.6111622384974937`*^9}, {3.6111627729992447`*^9, 3.611162794728648*^9}, {
   3.611162891753628*^9, 3.61116315822429*^9}, {3.611163201300222*^9, 
   3.611163288876153*^9}, {3.6111633844233713`*^9, 3.611163419799666*^9}, {
   3.6111635474392347`*^9, 3.611163689239029*^9}, {3.611163730916421*^9, 
   3.611163747140781*^9}, {3.611163781173532*^9, 3.611163861388054*^9}, {
   3.611163900422316*^9, 3.611163947547069*^9}, {3.6111642298056602`*^9, 
   3.611164246930952*^9}, 3.611164307117742*^9, {3.611164382393544*^9, 
   3.6111644908724413`*^9}, {3.611164522629056*^9, 3.6111645429261913`*^9}, 
   3.611164590410926*^9, {3.6111646255338783`*^9, 3.6111646446054*^9}, {
   3.611164792403199*^9, 3.611164826251396*^9}, {3.6111648900778217`*^9, 
   3.61116496830731*^9}, {3.61116500175616*^9, 3.611165036542562*^9}, {
   3.61116507062253*^9, 3.611165077883089*^9}, {3.611165197079905*^9, 
   3.6111652386310997`*^9}, {3.611374477158511*^9, 3.611374554008848*^9}, {
   3.6114148937888317`*^9, 3.611414919109997*^9}, 3.612096768806164*^9, {
   3.612096892636816*^9, 3.61209701504067*^9}, {3.612097071831416*^9, 
   3.612097112082941*^9}, {3.612108608639592*^9, 3.612108633107952*^9}, {
   3.61210866315874*^9, 3.6121087053833103`*^9}, {3.61210873673517*^9, 
   3.612108761596652*^9}, {3.612108845039351*^9, 3.612108899383665*^9}, {
   3.612109390719858*^9, 3.612109493110351*^9}, {3.612109686502378*^9, 
   3.612109702002121*^9}, {3.612109745958332*^9, 3.612109782344554*^9}, {
   3.612110086199441*^9, 3.612110103719861*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJzFm+VbVU/U9+mGo6SCCIoBIigYKCrrCEhKGT9CFANUQEFKSUFCkBaQ7hZQ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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-3.9955643896100494`, 4.}, {-0.21999377750243518`, 
   1.0199945199829947`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.611162022927827*^9, 3.611162035515938*^9}, {
   3.611162070881236*^9, 3.611162145513773*^9}, {3.611162203422757*^9, 
   3.6111622384974937`*^9}, {3.6111627729992447`*^9, 3.611162794728648*^9}, {
   3.611162891753628*^9, 3.61116315822429*^9}, {3.611163201300222*^9, 
   3.611163288876153*^9}, {3.6111633844233713`*^9, 3.611163419799666*^9}, {
   3.6111635474392347`*^9, 3.611163689239029*^9}, {3.611163730916421*^9, 
   3.611163747140781*^9}, {3.611163781173532*^9, 3.611163861388054*^9}, {
   3.611163900422316*^9, 3.611163947547069*^9}, {3.6111642298056602`*^9, 
   3.611164246930952*^9}, 3.611164307117742*^9, {3.611164382393544*^9, 
   3.6111644908724413`*^9}, {3.611164522629056*^9, 3.6111645429261913`*^9}, 
   3.611164590410926*^9, {3.6111646255338783`*^9, 3.6111646446054*^9}, {
   3.611164792403199*^9, 3.611164826251396*^9}, {3.6111648900778217`*^9, 
   3.61116496830731*^9}, {3.61116500175616*^9, 3.611165036542562*^9}, {
   3.61116507062253*^9, 3.611165077883089*^9}, {3.611165197079905*^9, 
   3.6111652386310997`*^9}, {3.611374477158511*^9, 3.611374554008848*^9}, {
   3.6114148937888317`*^9, 3.611414919109997*^9}, 3.612096768806164*^9, {
   3.612096892636816*^9, 3.61209701504067*^9}, {3.612097071831416*^9, 
   3.612097112082941*^9}, {3.612108608639592*^9, 3.612108633107952*^9}, {
   3.61210866315874*^9, 3.6121087053833103`*^9}, {3.61210873673517*^9, 
   3.612108761596652*^9}, {3.612108845039351*^9, 3.612108899383665*^9}, {
   3.612109390719858*^9, 3.612109493110351*^9}, {3.612109686502378*^9, 
   3.612109702002121*^9}, {3.612109745958332*^9, 3.612109782344554*^9}, {
   3.612110086199441*^9, 3.612110103734462*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw91mk0Ve/bB3BRzh6QeShDOZIoIVM5e++LqKgkQiVjEkohyViRIVFJRSRU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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJxF1nk4VVsfB/BjuOzDTaYM99Ap4UqlLtHg7L0Xr0r0KhT3Zp5KQofcblKK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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->NCache[{{0, 2 Pi}, {0., 1.}}, {{0, 6.283185307179586}, {0., 1.}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.611162022927827*^9, 3.611162035515938*^9}, {
   3.611162070881236*^9, 3.611162145513773*^9}, {3.611162203422757*^9, 
   3.6111622384974937`*^9}, {3.6111627729992447`*^9, 3.611162794728648*^9}, {
   3.611162891753628*^9, 3.61116315822429*^9}, {3.611163201300222*^9, 
   3.611163288876153*^9}, {3.6111633844233713`*^9, 3.611163419799666*^9}, {
   3.6111635474392347`*^9, 3.611163689239029*^9}, {3.611163730916421*^9, 
   3.611163747140781*^9}, {3.611163781173532*^9, 3.611163861388054*^9}, {
   3.611163900422316*^9, 3.611163947547069*^9}, {3.6111642298056602`*^9, 
   3.611164246930952*^9}, 3.611164307117742*^9, {3.611164382393544*^9, 
   3.6111644908724413`*^9}, {3.611164522629056*^9, 3.6111645429261913`*^9}, 
   3.611164590410926*^9, {3.6111646255338783`*^9, 3.6111646446054*^9}, {
   3.611164792403199*^9, 3.611164826251396*^9}, {3.6111648900778217`*^9, 
   3.61116496830731*^9}, {3.61116500175616*^9, 3.611165036542562*^9}, {
   3.61116507062253*^9, 3.611165077883089*^9}, {3.611165197079905*^9, 
   3.6111652386310997`*^9}, {3.611374477158511*^9, 3.611374554008848*^9}, {
   3.6114148937888317`*^9, 3.611414919109997*^9}, 3.612096768806164*^9, {
   3.612096892636816*^9, 3.61209701504067*^9}, {3.612097071831416*^9, 
   3.612097112082941*^9}, {3.612108608639592*^9, 3.612108633107952*^9}, {
   3.61210866315874*^9, 3.6121087053833103`*^9}, {3.61210873673517*^9, 
   3.612108761596652*^9}, {3.612108845039351*^9, 3.612108899383665*^9}, {
   3.612109390719858*^9, 3.612109493110351*^9}, {3.612109686502378*^9, 
   3.612109702002121*^9}, {3.612109745958332*^9, 3.612109782344554*^9}, {
   3.612110086199441*^9, 3.612110103744357*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"{", 
     RowBox[{
      RowBox[{"Cos", "[", "t", "]"}], ",", 
      RowBox[{"Sin", "[", "t", "]"}]}], "}"}], 
    SqrtBox[
     FractionBox[
      RowBox[{"1", "+", 
       RowBox[{"4", 
        SuperscriptBox[
         RowBox[{"Sin", "[", "t", "]"}], "40"]}]}], 
      RowBox[{
       SuperscriptBox[
        RowBox[{"Cos", "[", "t", "]"}], "2"], "+", 
       RowBox[{"4", 
        SuperscriptBox[
         RowBox[{"Sin", "[", "t", "]"}], "2"]}]}]]]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.6111633618908787`*^9, 3.611163372621564*^9}, {
  3.6111634271136827`*^9, 3.6111634816871767`*^9}, {3.611163873213697*^9, 
  3.6111638859166613`*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw0l3c8lm/0xyuJFJWspFLJTCIqomM1pKxQaA/pq2FEESFKIrLJ3js727H3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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-0.9999995325409373, 1.}, {-1.1180314321676155`, 
   1.1180317772375443`}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{{3.611163468039598*^9, 3.611163482692981*^9}, {
  3.611163874936088*^9, 
  3.611163886344104*^9}},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"Cos", "[", "t", "]"}], ",", 
     RowBox[{
      RowBox[{"1", "/", "5"}], " ", 
      RowBox[{"Sin", "[", "t", "]"}]}]}], "}"}], 
   RowBox[{"(", 
    RowBox[{"1", "+", 
     RowBox[{"1.1", 
      RowBox[{"(", 
       FractionBox["1", 
        RowBox[{
         SuperscriptBox["\[ExponentialE]", 
          RowBox[{"100", 
           RowBox[{"(", 
            RowBox[{"t", "-", "\[Pi]"}], ")"}]}]], "+", "1"}]], ")"}], 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "200"]}]}], ")"}]}], "//", 
  "Simplify"}]], "Input",
 CellChangeTimes->{{3.61141448365485*^9, 3.6114144919359503`*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{
    RowBox[{"Cos", "[", "t", "]"}], " ", 
    RowBox[{"(", 
     RowBox[{"1", "+", 
      FractionBox[
       RowBox[{"1.1`", " ", 
        SuperscriptBox[
         RowBox[{"Sin", "[", "t", "]"}], "200"]}], 
       RowBox[{"1", "+", 
        SuperscriptBox["\[ExponentialE]", 
         RowBox[{"100", " ", 
          RowBox[{"(", 
           RowBox[{
            RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]]}]]}], ")"}]}], ",", 
   RowBox[{
    FractionBox["1", "5"], " ", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{"Sin", "[", "t", "]"}], "+", 
      FractionBox[
       RowBox[{"1.1`", " ", 
        SuperscriptBox[
         RowBox[{"Sin", "[", "t", "]"}], "201"]}], 
       RowBox[{"1", "+", 
        SuperscriptBox["\[ExponentialE]", 
         RowBox[{"100", " ", 
          RowBox[{"(", 
           RowBox[{
            RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]]}]]}], ")"}]}]}], 
  "}"}]], "Output",
 CellChangeTimes->{3.611414504444601*^9, 3.6119253474369164`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"Cos", "[", "t", "]"}], 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], "200"]}], "//", "FullSimplify"}]], "Input",\

 CellChangeTimes->{{3.611414535990348*^9, 3.611414544590488*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Cos", "[", "t", "]"}], " ", 
  SuperscriptBox[
   RowBox[{"Sin", "[", "t", "]"}], "200"]}]], "Output",
 CellChangeTimes->{{3.611414538643976*^9, 3.6114145455915213`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"1.1", 
    RowBox[{"(", 
     FractionBox["1", 
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"100", 
         RowBox[{"(", 
          RowBox[{"t", "-", "\[Pi]"}], ")"}]}]], "+", "1"}]], ")"}]}], 
   "\[Equal]", "1"}], "//", "Reduce"}]], "Input",
 CellChangeTimes->{{3.611414837964464*^9, 3.611414840186564*^9}, 
   3.6114149608639917`*^9}],

Cell[BoxData[
 RowBox[{
  SuperscriptBox["\[ExponentialE]", 
   RowBox[{"100", " ", "t"}]], "\[Equal]", 
  "2.7392734247574934`*^135"}]], "Output",
 CellChangeTimes->{3.6114148406997547`*^9, 3.611414963431521*^9}]
}, Open  ]],

Cell[BoxData[{
 RowBox[{
  RowBox[{"f", 
   RowBox[{"(", "t", ")"}]}], " ", "=", " ", 
  RowBox[{"(", 
   RowBox[{"1", "+", 
    RowBox[{"c", " ", "sin", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", "t", ")"}], "p"], "/", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"d", " ", "exp", 
         RowBox[{"(", 
          RowBox[{"e", 
           RowBox[{"(", 
            RowBox[{"t", "-", "pi"}], ")"}]}], ")"}]}], "+", "1"}], 
       ")"}]}]}]}], ")"}]}], "\[IndentingNewLine]", 
 RowBox[{"x", "=", 
  RowBox[{"a", " ", "cos", 
   RowBox[{"(", "t", ")"}], "f", 
   RowBox[{"(", "t", ")"}]}]}], "\[IndentingNewLine]", 
 RowBox[{"y", "=", 
  RowBox[{"b", " ", "sin", 
   RowBox[{"(", "t", ")"}], "f", 
   RowBox[{"(", "t", ")"}]}]}], "\[IndentingNewLine]"}], "Input",
 CellChangeTimes->{{3.611415080918829*^9, 3.611415178603327*^9}, {
   3.611415210696662*^9, 3.6114152277639008`*^9}, {3.611415395619981*^9, 
   3.611415420165481*^9}, {3.611423486720784*^9, 3.611423500304922*^9}, 
   3.611512253101426*^9}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     FractionBox["1", 
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"100", 
         RowBox[{"(", 
          RowBox[{"t", "-", "\[Pi]"}], ")"}]}]], "+", "1"}]], ",", 
     RowBox[{
      RowBox[{"1", "/", "2"}], "-", 
      RowBox[{
       RowBox[{"1", "/", "2"}], 
       RowBox[{"Tanh", "[", 
        RowBox[{"100", 
         RowBox[{"(", 
          RowBox[{"t", "-", "\[Pi]"}], ")"}]}], "]"}]}]}], ",", 
     RowBox[{"Sech", "[", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}], "]"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.6121034346334057`*^9, 3.612103450432815*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJw91mk0Ve/bB3BRzh6QeShDOZIoIVM5e++LqKgkQiVjEkohyViRIVFJRSRU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     "]]}, 
   {Hue[0.9060679774997897, 0.6, 0.6], LineBox[CompressedData["
1:eJxF1nk4VVsfB/BjuOzDTaYM99Ap4UqlLtHg7L0Xr0r0KhT3Zp5KQofcblKK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     "]]}, 
   {Hue[0.1421359549995791, 0.6, 0.6], LineBox[CompressedData["
1:eJwt13k4VH0bB3BZZs4ZZGcG5aGoVNqVLPedskSPUGlF1kSEbKWSp2ypbCUp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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->NCache[{{0, 2 Pi}, {0., 1.}}, {{0, 6.283185307179586}, {0., 1.}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{3.612103453944047*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{"u", "=."}]], "Input",
 CellChangeTimes->{{3.612097295717802*^9, 3.612097297424695*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  SuperscriptBox["a", "2"], 
  SqrtBox["a"]}]], "Input",
 CellChangeTimes->{3.612117563040464*^9}],

Cell[BoxData[
 SuperscriptBox["a", 
  RowBox[{"5", "/", "2"}]]], "Output",
 CellChangeTimes->{3.612117563729258*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{
    FractionBox[
     SuperscriptBox[
      RowBox[{"Cos", "[", 
       RowBox[{
        FractionBox["\[Pi]", "4"], "+", 
        FractionBox["t", "a"]}], "]"}], "2"], 
     SuperscriptBox[
      RowBox[{"Sin", "[", 
       RowBox[{
        FractionBox["\[Pi]", "4"], "+", 
        FractionBox["t", "a"]}], "]"}], "2"]], "/.", 
    RowBox[{"a", "\[Rule]", "2"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "*", "\[Pi]"}]}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.612118697076015*^9, 3.612118710119529*^9}, {
  3.612118744069004*^9, 3.6121187851907473`*^9}, {3.612119948924803*^9, 
  3.612119956434668*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVV3k4ll8TtmVf3s1OIUn2hCTMWMq+C9kJSX5CSLYWEpIQQokUoZAtRKFS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     "]]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->
   NCache[{{0, 2 Pi}, {6.089439791684044*^-8, 1.4205873275153494`*^7}}, {{
     0, 6.283185307179586}, {6.089439791684044*^-8, 1.4205873275153494`*^7}}],
  
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{
  3.612118711105411*^9, {3.61211874640499*^9, 3.612118790570306*^9}, 
   3.6121199621656923`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"u", "=", 
   RowBox[{"(", 
    RowBox[{"1", "+", 
     RowBox[{"c", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           RowBox[{"t", "/", "a"}], "]"}], "+", 
          RowBox[{"Sin", "[", 
           RowBox[{"t", "/", "a"}], "]"}]}], 
         SqrtBox["a"]], ")"}], "p"]}]}], ")"}]}], "\[IndentingNewLine]", 
  RowBox[{"(*", "*)"}], 
  RowBox[{"(*", 
   RowBox[{"u", "=", 
    RowBox[{"(", 
     RowBox[{"1", "+", 
      RowBox[{"a", " ", 
       SuperscriptBox[
        RowBox[{"Sin", "[", 
         RowBox[{
          RowBox[{"t", "/", "a"}], "+", 
          FractionBox["\[Pi]", "4"]}], "]"}], "p"]}]}], ")"}]}], 
   "*)"}]}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", "t"}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "2"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "3"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "4"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "5"}], "}"}]}], "]"}]}], "Input",
 CellChangeTimes->{{3.612116048844754*^9, 3.612116063285673*^9}, {
   3.612116403249111*^9, 3.612116425574985*^9}, {3.612116485442583*^9, 
   3.6121164901351833`*^9}, {3.612116641695002*^9, 3.612116642344429*^9}, {
   3.6121168547304907`*^9, 3.612116856763801*^9}, 3.6121172055726557`*^9, {
   3.612117500203335*^9, 3.612117520478796*^9}, {3.612117589623212*^9, 
   3.6121176087736473`*^9}, {3.6121176506928253`*^9, 3.612117655451605*^9}, {
   3.612117735402524*^9, 3.612117755488556*^9}, {3.6121182272675734`*^9, 
   3.612118256267037*^9}, {3.6121195047100973`*^9, 3.612119516821713*^9}, {
   3.612119554336849*^9, 3.612119586043351*^9}, {3.6121196483793488`*^9, 
   3.612119657284246*^9}, 3.612119723863665*^9, {3.612119805779593*^9, 
   3.6121198530938263`*^9}, {3.6121201619550047`*^9, 
   3.6121202058789053`*^9}, {3.6121227547407227`*^9, 3.612122760954756*^9}, {
   3.612122810142591*^9, 3.6121228117977962`*^9}}],

Cell[BoxData[
 RowBox[{"1", "+", 
  RowBox[{"c", " ", 
   SuperscriptBox[
    RowBox[{"(", 
     FractionBox[
      RowBox[{
       RowBox[{"Cos", "[", 
        FractionBox["t", "a"], "]"}], "+", 
       RowBox[{"Sin", "[", 
        FractionBox["t", "a"], "]"}]}], 
      SqrtBox["a"]], ")"}], "p"]}]}]], "Output",
 CellChangeTimes->{
  3.6121160641582203`*^9, 3.61211643102131*^9, 3.612116498025311*^9, 
   3.6121166427765713`*^9, 3.612116857473782*^9, 3.612117205987071*^9, {
   3.612117503553536*^9, 3.612117525770276*^9}, 3.612117609523044*^9, 
   3.6121176569316998`*^9, {3.612117739650316*^9, 3.612117757561132*^9}, 
   3.612118256769557*^9, 3.6121195183167973`*^9, {3.6121195655338097`*^9, 
   3.612119589626891*^9}, 3.612119660069384*^9, 3.6121197245497847`*^9, {
   3.61211980766208*^9, 3.6121198535337887`*^9}, {3.612120169682345*^9, 
   3.6121202079600153`*^9}, 3.6121227699762*^9, {3.612122803029707*^9, 
   3.6121228125123987`*^9}}],

Cell[BoxData[
 FractionBox[
  RowBox[{"c", " ", "p", " ", 
   SuperscriptBox[
    RowBox[{"(", 
     FractionBox[
      RowBox[{
       RowBox[{"Cos", "[", 
        FractionBox["t", "a"], "]"}], "+", 
       RowBox[{"Sin", "[", 
        FractionBox["t", "a"], "]"}]}], 
      SqrtBox["a"]], ")"}], 
    RowBox[{
     RowBox[{"-", "1"}], "+", "p"}]], " ", 
   RowBox[{"(", 
    RowBox[{
     FractionBox[
      RowBox[{"Cos", "[", 
       FractionBox["t", "a"], "]"}], "a"], "-", 
     FractionBox[
      RowBox[{"Sin", "[", 
       FractionBox["t", "a"], "]"}], "a"]}], ")"}]}], 
  SqrtBox["a"]]], "Output",
 CellChangeTimes->{
  3.6121160641582203`*^9, 3.61211643102131*^9, 3.612116498025311*^9, 
   3.6121166427765713`*^9, 3.612116857473782*^9, 3.612117205987071*^9, {
   3.612117503553536*^9, 3.612117525770276*^9}, 3.612117609523044*^9, 
   3.6121176569316998`*^9, {3.612117739650316*^9, 3.612117757561132*^9}, 
   3.612118256769557*^9, 3.6121195183167973`*^9, {3.6121195655338097`*^9, 
   3.612119589626891*^9}, 3.612119660069384*^9, 3.6121197245497847`*^9, {
   3.61211980766208*^9, 3.6121198535337887`*^9}, {3.612120169682345*^9, 
   3.6121202079600153`*^9}, 3.6121227699762*^9, {3.612122803029707*^9, 
   3.612122812521223*^9}}],

Cell[BoxData[
 RowBox[{"c", " ", 
  RowBox[{"(", 
   RowBox[{
    FractionBox[
     RowBox[{"p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "2"]]}], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "2"]]}], ")"}]}], 
     SqrtBox["a"]], "+", 
    FractionBox[
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "a"], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], "a"]}], ")"}], "2"]}], "a"]}], 
   ")"}]}]], "Output",
 CellChangeTimes->{
  3.6121160641582203`*^9, 3.61211643102131*^9, 3.612116498025311*^9, 
   3.6121166427765713`*^9, 3.612116857473782*^9, 3.612117205987071*^9, {
   3.612117503553536*^9, 3.612117525770276*^9}, 3.612117609523044*^9, 
   3.6121176569316998`*^9, {3.612117739650316*^9, 3.612117757561132*^9}, 
   3.612118256769557*^9, 3.6121195183167973`*^9, {3.6121195655338097`*^9, 
   3.612119589626891*^9}, 3.612119660069384*^9, 3.6121197245497847`*^9, {
   3.61211980766208*^9, 3.6121198535337887`*^9}, {3.612120169682345*^9, 
   3.6121202079600153`*^9}, 3.6121227699762*^9, {3.612122803029707*^9, 
   3.6121228125300503`*^9}}],

Cell[BoxData[
 RowBox[{"c", " ", 
  RowBox[{"(", 
   RowBox[{
    FractionBox[
     RowBox[{"p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "3"]]}], "+", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "3"]]}], ")"}]}], 
     SqrtBox["a"]], "+", 
    FractionBox[
     RowBox[{"3", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "2"]]}], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "2"]]}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        FractionBox[
         RowBox[{"Cos", "[", 
          FractionBox["t", "a"], "]"}], "a"], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], "a"]}], ")"}]}], "a"], "+", 
    FractionBox[
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "a"], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], "a"]}], ")"}], "3"]}], 
     SuperscriptBox["a", 
      RowBox[{"3", "/", "2"}]]]}], ")"}]}]], "Output",
 CellChangeTimes->{
  3.6121160641582203`*^9, 3.61211643102131*^9, 3.612116498025311*^9, 
   3.6121166427765713`*^9, 3.612116857473782*^9, 3.612117205987071*^9, {
   3.612117503553536*^9, 3.612117525770276*^9}, 3.612117609523044*^9, 
   3.6121176569316998`*^9, {3.612117739650316*^9, 3.612117757561132*^9}, 
   3.612118256769557*^9, 3.6121195183167973`*^9, {3.6121195655338097`*^9, 
   3.612119589626891*^9}, 3.612119660069384*^9, 3.6121197245497847`*^9, {
   3.61211980766208*^9, 3.6121198535337887`*^9}, {3.612120169682345*^9, 
   3.6121202079600153`*^9}, 3.6121227699762*^9, {3.612122803029707*^9, 
   3.6121228125384483`*^9}}],

Cell[BoxData[
 RowBox[{"c", " ", 
  RowBox[{"(", 
   RowBox[{
    FractionBox[
     RowBox[{"p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        FractionBox[
         RowBox[{"Cos", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "4"]], "+", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "4"]]}], ")"}]}], 
     SqrtBox["a"]], "+", 
    FractionBox[
     RowBox[{"3", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", 
          FractionBox[
           RowBox[{"Cos", "[", 
            FractionBox["t", "a"], "]"}], 
           SuperscriptBox["a", "2"]]}], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "2"]]}], ")"}], "2"]}], "a"], "+", 
    FractionBox[
     RowBox[{"4", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "3"]]}], "+", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "3"]]}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        FractionBox[
         RowBox[{"Cos", "[", 
          FractionBox["t", "a"], "]"}], "a"], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], "a"]}], ")"}]}], "a"], "+", 
    FractionBox[
     RowBox[{"6", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "2"]]}], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "2"]]}], ")"}], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "a"], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], "a"]}], ")"}], "2"]}], 
     SuperscriptBox["a", 
      RowBox[{"3", "/", "2"}]]], "+", 
    FractionBox[
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "4"}], "+", "p"}]], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "a"], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], "a"]}], ")"}], "4"]}], 
     SuperscriptBox["a", "2"]]}], ")"}]}]], "Output",
 CellChangeTimes->{
  3.6121160641582203`*^9, 3.61211643102131*^9, 3.612116498025311*^9, 
   3.6121166427765713`*^9, 3.612116857473782*^9, 3.612117205987071*^9, {
   3.612117503553536*^9, 3.612117525770276*^9}, 3.612117609523044*^9, 
   3.6121176569316998`*^9, {3.612117739650316*^9, 3.612117757561132*^9}, 
   3.612118256769557*^9, 3.6121195183167973`*^9, {3.6121195655338097`*^9, 
   3.612119589626891*^9}, 3.612119660069384*^9, 3.6121197245497847`*^9, {
   3.61211980766208*^9, 3.6121198535337887`*^9}, {3.612120169682345*^9, 
   3.6121202079600153`*^9}, 3.6121227699762*^9, {3.612122803029707*^9, 
   3.61212281254782*^9}}],

Cell[BoxData[
 RowBox[{"c", " ", 
  RowBox[{"(", 
   RowBox[{
    FractionBox[
     RowBox[{"p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        FractionBox[
         RowBox[{"Cos", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "5"]], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "5"]]}], ")"}]}], 
     SqrtBox["a"]], "+", 
    FractionBox[
     RowBox[{"10", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "3"]]}], "+", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "3"]]}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "2"]]}], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "2"]]}], ")"}]}], "a"], "+", 
    FractionBox[
     RowBox[{"5", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        FractionBox[
         RowBox[{"Cos", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "4"]], "+", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "4"]]}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        FractionBox[
         RowBox[{"Cos", "[", 
          FractionBox["t", "a"], "]"}], "a"], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], "a"]}], ")"}]}], "a"], "+", 
    FractionBox[
     RowBox[{"15", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", 
          FractionBox[
           RowBox[{"Cos", "[", 
            FractionBox["t", "a"], "]"}], 
           SuperscriptBox["a", "2"]]}], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "2"]]}], ")"}], "2"], " ", 
      RowBox[{"(", 
       RowBox[{
        FractionBox[
         RowBox[{"Cos", "[", 
          FractionBox["t", "a"], "]"}], "a"], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], "a"]}], ")"}]}], 
     SuperscriptBox["a", 
      RowBox[{"3", "/", "2"}]]], "+", 
    FractionBox[
     RowBox[{"10", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "3"]]}], "+", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "3"]]}], ")"}], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "a"], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], "a"]}], ")"}], "2"]}], 
     SuperscriptBox["a", 
      RowBox[{"3", "/", "2"}]]], "+", 
    FractionBox[
     RowBox[{"10", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "4"}], "+", "p"}]], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", 
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], 
          SuperscriptBox["a", "2"]]}], "-", 
        FractionBox[
         RowBox[{"Sin", "[", 
          FractionBox["t", "a"], "]"}], 
         SuperscriptBox["a", "2"]]}], ")"}], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "a"], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], "a"]}], ")"}], "3"]}], 
     SuperscriptBox["a", "2"]], "+", 
    FractionBox[
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "4"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        FractionBox[
         RowBox[{
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "+", 
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}]}], 
         SqrtBox["a"]], ")"}], 
       RowBox[{
        RowBox[{"-", "5"}], "+", "p"}]], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         FractionBox[
          RowBox[{"Cos", "[", 
           FractionBox["t", "a"], "]"}], "a"], "-", 
         FractionBox[
          RowBox[{"Sin", "[", 
           FractionBox["t", "a"], "]"}], "a"]}], ")"}], "5"]}], 
     SuperscriptBox["a", 
      RowBox[{"5", "/", "2"}]]]}], ")"}]}]], "Output",
 CellChangeTimes->{
  3.6121160641582203`*^9, 3.61211643102131*^9, 3.612116498025311*^9, 
   3.6121166427765713`*^9, 3.612116857473782*^9, 3.612117205987071*^9, {
   3.612117503553536*^9, 3.612117525770276*^9}, 3.612117609523044*^9, 
   3.6121176569316998`*^9, {3.612117739650316*^9, 3.612117757561132*^9}, 
   3.612118256769557*^9, 3.6121195183167973`*^9, {3.6121195655338097`*^9, 
   3.612119589626891*^9}, 3.612119660069384*^9, 3.6121197245497847`*^9, {
   3.61211980766208*^9, 3.6121198535337887`*^9}, {3.612120169682345*^9, 
   3.6121202079600153`*^9}, 3.6121227699762*^9, {3.612122803029707*^9, 
   3.612122812555072*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(*", 
   RowBox[{"u", "=", 
    RowBox[{"1", "+", 
     RowBox[{"c", 
      RowBox[{"(", 
       FractionBox["1", 
        RowBox[{
         RowBox[{"d", " ", 
          SuperscriptBox["\[ExponentialE]", 
           RowBox[{"e", 
            RowBox[{"(", 
             RowBox[{"t", "-", "\[Pi]"}], ")"}]}]]}], "+", "1"}]], ")"}], 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}]}]}], "*)"}], 
  "\[IndentingNewLine]", 
  RowBox[{
   RowBox[{"u", "=", 
    RowBox[{"1", "+", 
     RowBox[{"c", " ", 
      RowBox[{"Sf", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}]}]}], "\[IndentingNewLine]", 
   RowBox[{"D", "[", 
    RowBox[{"u", ",", "t"}], "]"}], "\[IndentingNewLine]", 
   RowBox[{
    RowBox[{
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", "2"}], "}"}]}], "]"}], "==", " ", 
     RowBox[{
      RowBox[{
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", "c", " ", 
       RowBox[{"Sf", "[", "t", "]"}], 
       SuperscriptBox[
        RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
       SuperscriptBox[
        RowBox[{"Sin", "[", "t", "]"}], 
        RowBox[{
         RowBox[{"-", "2"}], "+", "p"}]]}], "+", 
      RowBox[{"2", " ", "c", " ", "p", " ", 
       RowBox[{"Cos", "[", "t", "]"}], " ", 
       SuperscriptBox[
        RowBox[{"Sin", "[", "t", "]"}], 
        RowBox[{
         RowBox[{"-", "1"}], "+", "p"}]], " ", 
       RowBox[{
        SuperscriptBox["Sf", "\[Prime]",
         MultilineFunction->None], "[", "t", "]"}]}], "+", 
      RowBox[{"c", " ", 
       SuperscriptBox[
        RowBox[{"Sin", "[", "t", "]"}], "p"], " ", 
       RowBox[{
        SuperscriptBox["Sf", "\[Prime]\[Prime]",
         MultilineFunction->None], "[", "t", "]"}]}], "-", 
      RowBox[{"p", " ", 
       RowBox[{"(", 
        RowBox[{"u", "-", "1"}], ")"}]}]}]}], "//", "Simplify"}], 
   "\[IndentingNewLine]", 
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "3"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "4"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "5"}], "}"}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.6119273891443653`*^9, 3.6119274296439457`*^9}, {
  3.612009234966072*^9, 3.612009240297978*^9}, {3.612097151460142*^9, 
  3.6120971549951887`*^9}, {3.612097224997369*^9, 3.612097232697179*^9}, {
  3.612097268126639*^9, 3.612097268654551*^9}, {3.61210327182996*^9, 
  3.6121032742257423`*^9}, {3.61210613999621*^9, 3.612106190831955*^9}, {
  3.61210661069088*^9, 3.612106693116949*^9}, {3.6121068042560463`*^9, 
  3.6121068065900803`*^9}}],

Cell[BoxData[
 RowBox[{"1", "+", 
  RowBox[{"c", " ", 
   RowBox[{"Sf", "[", "t", "]"}], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], "p"]}]}]], "Output",
 CellChangeTimes->{
  3.61192743063448*^9, 3.612009242036148*^9, 3.612097271509934*^9, {
   3.612103261449562*^9, 3.612103276727007*^9}, {3.612106174524796*^9, 
   3.61210619212017*^9}, 3.612106393923223*^9, {3.612106615436558*^9, 
   3.612106694061166*^9}, 3.612106807179501*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"c", " ", "p", " ", 
   RowBox[{"Cos", "[", "t", "]"}], " ", 
   RowBox[{"Sf", "[", "t", "]"}], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], 
    RowBox[{
     RowBox[{"-", "1"}], "+", "p"}]]}], "+", 
  RowBox[{"c", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], "p"], " ", 
   RowBox[{
    SuperscriptBox["Sf", "\[Prime]",
     MultilineFunction->None], "[", "t", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.61192743063448*^9, 3.612009242036148*^9, 3.612097271509934*^9, {
   3.612103261449562*^9, 3.612103276727007*^9}, {3.612106174524796*^9, 
   3.61210619212017*^9}, 3.612106393923223*^9, {3.612106615436558*^9, 
   3.612106694061166*^9}, 3.61210680718323*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.61192743063448*^9, 3.612009242036148*^9, 3.612097271509934*^9, {
   3.612103261449562*^9, 3.612103276727007*^9}, {3.612106174524796*^9, 
   3.61210619212017*^9}, 3.612106393923223*^9, {3.612106615436558*^9, 
   3.612106694061166*^9}, 3.612106807186027*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"c", " ", 
   RowBox[{"Sf", "[", "t", "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "3"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]]}], "-", 
     RowBox[{"2", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}], "-", 
     RowBox[{
      SuperscriptBox["p", "2"], " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}]}], ")"}]}], "+", 
  RowBox[{"3", " ", "c", " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "-", 
     RowBox[{"p", " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}]}], ")"}], " ", 
   RowBox[{
    SuperscriptBox["Sf", "\[Prime]",
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"3", " ", "c", " ", "p", " ", 
   RowBox[{"Cos", "[", "t", "]"}], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], 
    RowBox[{
     RowBox[{"-", "1"}], "+", "p"}]], " ", 
   RowBox[{
    SuperscriptBox["Sf", "\[Prime]\[Prime]",
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"c", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], "p"], " ", 
   RowBox[{
    SuperscriptBox["Sf", 
     TagBox[
      RowBox[{"(", "3", ")"}],
      Derivative],
     MultilineFunction->None], "[", "t", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.61192743063448*^9, 3.612009242036148*^9, 3.612097271509934*^9, {
   3.612103261449562*^9, 3.612103276727007*^9}, {3.612106174524796*^9, 
   3.61210619212017*^9}, 3.612106393923223*^9, {3.612106615436558*^9, 
   3.612106694061166*^9}, 3.612106807189856*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"c", " ", 
   RowBox[{"Sf", "[", "t", "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "4"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "4"}], "+", "p"}]]}], "-", 
     RowBox[{"3", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "-", 
     RowBox[{"2", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "1"}], "+", "p"}], ")"}], "2"], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "-", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", 
      SuperscriptBox["p", "2"], " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "+", 
     RowBox[{"2", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}], "+", 
     RowBox[{
      SuperscriptBox["p", "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}]}], ")"}]}], "+", 
  RowBox[{"4", " ", "c", " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "3"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]]}], "-", 
     RowBox[{"2", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}], "-", 
     RowBox[{
      SuperscriptBox["p", "2"], " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}]}], ")"}], " ", 
   RowBox[{
    SuperscriptBox["Sf", "\[Prime]",
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"6", " ", "c", " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "-", 
     RowBox[{"p", " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}]}], ")"}], " ", 
   RowBox[{
    SuperscriptBox["Sf", "\[Prime]\[Prime]",
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"4", " ", "c", " ", "p", " ", 
   RowBox[{"Cos", "[", "t", "]"}], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], 
    RowBox[{
     RowBox[{"-", "1"}], "+", "p"}]], " ", 
   RowBox[{
    SuperscriptBox["Sf", 
     TagBox[
      RowBox[{"(", "3", ")"}],
      Derivative],
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"c", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], "p"], " ", 
   RowBox[{
    SuperscriptBox["Sf", 
     TagBox[
      RowBox[{"(", "4", ")"}],
      Derivative],
     MultilineFunction->None], "[", "t", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.61192743063448*^9, 3.612009242036148*^9, 3.612097271509934*^9, {
   3.612103261449562*^9, 3.612103276727007*^9}, {3.612106174524796*^9, 
   3.61210619212017*^9}, 3.612106393923223*^9, {3.612106615436558*^9, 
   3.612106694061166*^9}, 3.612106807194962*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"c", " ", 
   RowBox[{"Sf", "[", "t", "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "4"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "5"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "5"}], "+", "p"}]]}], "-", 
     RowBox[{"4", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "3"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]]}], "-", 
     RowBox[{"3", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "2"}], "+", "p"}], ")"}], "2"], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "3"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]]}], "-", 
     RowBox[{"2", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "1"}], "+", "p"}], ")"}], "2"], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "3"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]]}], "-", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", 
      SuperscriptBox["p", "2"], " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "3"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]]}], "+", 
     RowBox[{"6", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}], "+", 
     RowBox[{"4", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "1"}], "+", "p"}], ")"}], "2"], " ", "p", " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}], "+", 
     RowBox[{"4", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", 
      SuperscriptBox["p", "2"], " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}], "+", 
     RowBox[{
      SuperscriptBox["p", "3"], " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}]}], ")"}]}], "+", 
  RowBox[{"5", " ", "c", " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "4"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "4"}], "+", "p"}]]}], "-", 
     RowBox[{"3", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "-", 
     RowBox[{"2", " ", 
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "1"}], "+", "p"}], ")"}], "2"], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "-", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", 
      SuperscriptBox["p", "2"], " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "+", 
     RowBox[{"2", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}], "+", 
     RowBox[{
      SuperscriptBox["p", "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}]}], ")"}], " ", 
   RowBox[{
    SuperscriptBox["Sf", "\[Prime]",
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"10", " ", "c", " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}], ")"}], " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "3"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "3"}], "+", "p"}]]}], "-", 
     RowBox[{"2", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}], "-", 
     RowBox[{
      SuperscriptBox["p", "2"], " ", 
      RowBox[{"Cos", "[", "t", "]"}], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}]]}]}], ")"}], " ", 
   RowBox[{
    SuperscriptBox["Sf", "\[Prime]\[Prime]",
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"10", " ", "c", " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "1"}], "+", "p"}], ")"}], " ", "p", " ", 
      SuperscriptBox[
       RowBox[{"Cos", "[", "t", "]"}], "2"], " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], 
       RowBox[{
        RowBox[{"-", "2"}], "+", "p"}]]}], "-", 
     RowBox[{"p", " ", 
      SuperscriptBox[
       RowBox[{"Sin", "[", "t", "]"}], "p"]}]}], ")"}], " ", 
   RowBox[{
    SuperscriptBox["Sf", 
     TagBox[
      RowBox[{"(", "3", ")"}],
      Derivative],
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"5", " ", "c", " ", "p", " ", 
   RowBox[{"Cos", "[", "t", "]"}], " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], 
    RowBox[{
     RowBox[{"-", "1"}], "+", "p"}]], " ", 
   RowBox[{
    SuperscriptBox["Sf", 
     TagBox[
      RowBox[{"(", "4", ")"}],
      Derivative],
     MultilineFunction->None], "[", "t", "]"}]}], "+", 
  RowBox[{"c", " ", 
   SuperscriptBox[
    RowBox[{"Sin", "[", "t", "]"}], "p"], " ", 
   RowBox[{
    SuperscriptBox["Sf", 
     TagBox[
      RowBox[{"(", "5", ")"}],
      Derivative],
     MultilineFunction->None], "[", "t", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.61192743063448*^9, 3.612009242036148*^9, 3.612097271509934*^9, {
   3.612103261449562*^9, 3.612103276727007*^9}, {3.612106174524796*^9, 
   3.61210619212017*^9}, 3.612106393923223*^9, {3.612106615436558*^9, 
   3.612106694061166*^9}, 3.612106807204516*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{
   FractionBox[
    RowBox[{"c", " ", "d", " ", "e", " ", 
     SuperscriptBox["\[ExponentialE]", 
      RowBox[{"e", " ", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]], " ", 
     SuperscriptBox[
      RowBox[{"Sin", "[", "t", "]"}], "p"]}], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{"1", "+", 
       RowBox[{"d", " ", 
        SuperscriptBox["\[ExponentialE]", 
         RowBox[{"e", " ", 
          RowBox[{"(", 
           RowBox[{
            RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]]}]}], ")"}], "2"]], "==", 
   RowBox[{
    FractionBox[
     RowBox[{"d", " ", "e", " ", 
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{"e", " ", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]], " "}], 
     RowBox[{"1", "+", 
      RowBox[{"d", " ", 
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"e", " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]]}]}]], 
    RowBox[{"(", 
     RowBox[{"u", "-", "1"}], ")"}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  FractionBox[
   RowBox[{"c", " ", "p", " ", 
    RowBox[{"Cos", "[", "t", "]"}], " ", 
    SuperscriptBox[
     RowBox[{"Sin", "[", "t", "]"}], 
     RowBox[{
      RowBox[{"-", "1"}], "+", "p"}]]}], 
   RowBox[{"1", "+", 
    RowBox[{"d", " ", 
     SuperscriptBox["\[ExponentialE]", 
      RowBox[{"e", " ", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]]}]}]], "\[Equal]", 
  RowBox[{"p", " ", 
   RowBox[{"Cot", "[", "t", "]"}], 
   RowBox[{"(", 
    RowBox[{"u", "-", "1"}], ")"}]}]}]}], "Input",
 CellChangeTimes->{{3.611927725939332*^9, 3.611927789044043*^9}, {
  3.611927862735216*^9, 3.611927931853362*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{{3.611927745770932*^9, 3.611927769673581*^9}, {
  3.611927878036343*^9, 3.611927933070836*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{{3.611927745770932*^9, 3.611927769673581*^9}, {
  3.611927878036343*^9, 3.611927933074319*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"(", 
   RowBox[{
    RowBox[{"p", " ", 
     RowBox[{"Cot", "[", "t", "]"}]}], "+", 
    FractionBox[
     RowBox[{"d", " ", "e", " ", 
      SuperscriptBox["\[ExponentialE]", 
       RowBox[{"e", " ", 
        RowBox[{"(", 
         RowBox[{
          RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]], " "}], 
     RowBox[{"1", "+", 
      RowBox[{"d", " ", 
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"e", " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}]]}]}]]}], ")"}], "//", 
  "FullSimplify"}]], "Input",
 CellChangeTimes->{{3.611927796930664*^9, 3.611927799843429*^9}, {
  3.611928037915084*^9, 3.61192805538186*^9}}],

Cell[BoxData[
 RowBox[{
  FractionBox[
   RowBox[{"d", " ", "e", " ", 
    SuperscriptBox["\[ExponentialE]", 
     RowBox[{"e", " ", "t"}]]}], 
   RowBox[{
    SuperscriptBox["\[ExponentialE]", 
     RowBox[{"e", " ", "\[Pi]"}]], "+", 
    RowBox[{"d", " ", 
     SuperscriptBox["\[ExponentialE]", 
      RowBox[{"e", " ", "t"}]]}]}]], "+", 
  RowBox[{"p", " ", 
   RowBox[{"Cot", "[", "t", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.611927800511334*^9, {3.6119280474226627`*^9, 3.611928056797987*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{"Cos", "[", "t", "]"}], "/", 
  RowBox[{"Sin", "[", "t", "]"}]}]], "Input",
 CellChangeTimes->{{3.611927899571797*^9, 3.61192790411934*^9}}],

Cell[BoxData[
 RowBox[{"Cot", "[", "t", "]"}]], "Output",
 CellChangeTimes->{3.611927904559754*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot", "[", 
  RowBox[{
   RowBox[{"Cot", "[", "t", "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", 
     RowBox[{"-", "\[Pi]"}], ",", "\[Pi]"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.611927944853709*^9, 3.6119279611692467`*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJwVjHk81Pkfx+cex5TckS3Z1YaSu5odvt8k3Yg2sjooFSkhEV3Isc4siSIp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     "]], LineBox[CompressedData["
1:eJwVlndYjY0fxk9nPS3VqeNUZCWRqBDJ6PstokgviRQq3kKUqEQliXahgQZp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     "]], 
    LineBox[{{-0.0009475965760193097, -6.4871036435983545`}, \
{-0.0009387012790420306, 6.405900405871024}}]}},
  AspectRatio->NCache[GoldenRatio^(-1), 0.6180339887498948],
  Axes->True,
  AxesLabel->{None, None},
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->
   NCache[{{-Pi, Pi}, {-6.4871036435983545`, 
     6.405900405871024}}, {{-3.141592653589793, 
    3.141592653589793}, {-6.4871036435983545`, 6.405900405871024}}],
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{
  3.611927961774067*^9},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"-", 
    FractionBox["4", "5"]}], "+", 
   FractionBox["4", "12"], "-", 
   FractionBox["5", "3"]}], "//", "N"}]], "Input",
 CellChangeTimes->{{3.611940137826335*^9, 3.6119401525391903`*^9}, {
  3.611940263068561*^9, 3.611940263578898*^9}}],

Cell[BoxData[
 RowBox[{"-", "2.1333333333333333`"}]], "Output",
 CellChangeTimes->{3.611940153092375*^9, 3.6119402641516857`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"1.1", "/", "2"}]], "Input",
 CellChangeTimes->{{3.6120971241457663`*^9, 3.6120971249423428`*^9}}],

Cell[BoxData["0.55`"], "Output",
 CellChangeTimes->{3.612097125330717*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"-", "4"}], " ", 
   SuperscriptBox["e", "4"], " ", 
   SuperscriptBox[
    RowBox[{"Sech", "[", 
     RowBox[{"e", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}], "]"}], "4"], 
   RowBox[{"(", 
    RowBox[{"1", "-", 
     RowBox[{"2", "u"}]}], ")"}]}], "\[Equal]", " ", 
  RowBox[{"8", 
   FractionBox["e", "d"], 
   RowBox[{"D", "[", 
    RowBox[{"u", ",", "t"}], "]"}], 
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "2"}], "}"}]}], "]"}]}]}]], "Input",
 CellChangeTimes->{{3.6121049407297983`*^9, 3.612104945590106*^9}, {
  3.6121053270333643`*^9, 3.612105376908634*^9}, {3.612105446757244*^9, 
  3.6121054534947653`*^9}, {3.612105555010312*^9, 3.612105581816092*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{3.612104946039029*^9, 3.612105377774309*^9, 
  3.612105454300919*^9, 3.6121055827877007`*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"u", "=", 
  FractionBox[
   RowBox[{"1", "-", 
    RowBox[{"d", " ", 
     RowBox[{"Tanh", "[", 
      RowBox[{"e", 
       RowBox[{"(", 
        RowBox[{"t", "-", "\[Pi]"}], ")"}]}], "]"}]}]}], 
   "2"]}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", "t"}], "]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "2"}], "}"}]}], "]"}], "\[Equal]", 
   RowBox[{
    RowBox[{"-", "2"}], 
    FractionBox["e", "d"], 
    RowBox[{"D", "[", 
     RowBox[{"u", ",", "t"}], "]"}], " ", 
    RowBox[{"(", 
     RowBox[{"1", "-", 
      RowBox[{"2", "u"}]}], ")"}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "3"}], "}"}]}], "]"}], "==", " ", 
   RowBox[{
    RowBox[{"4", 
     FractionBox["e", "d"], 
     SuperscriptBox[
      RowBox[{"D", "[", 
       RowBox[{"u", ",", "t"}], "]"}], "2"]}], "-", " ", 
    RowBox[{"2", " ", 
     FractionBox["e", "d"], "  ", 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", "2"}], "}"}]}], "]"}], 
     RowBox[{"(", 
      RowBox[{"1", "-", 
       RowBox[{"2", "u"}]}], ")"}]}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "4"}], "}"}]}], "]"}], "\[Equal]", 
   RowBox[{
    RowBox[{"12", " ", 
     FractionBox["e", "d"], "  ", 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", "2"}], "}"}]}], "]"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", "t"}], "]"}]}], "-", " ", 
    RowBox[{"2", " ", 
     FractionBox["e", "d"], "  ", 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", "3"}], "}"}]}], "]"}], 
     RowBox[{"(", 
      RowBox[{"1", "-", 
       RowBox[{"2", "u"}]}], ")"}]}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"t", ",", "5"}], "}"}]}], "]"}], "\[Equal]", 
   RowBox[{
    RowBox[{"16", " ", 
     FractionBox["e", "d"], "  ", 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", "3"}], "}"}]}], "]"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", "t"}], "]"}]}], "+", 
    RowBox[{"12", " ", 
     FractionBox["e", "d"], "  ", 
     SuperscriptBox[
      RowBox[{"D", "[", 
       RowBox[{"u", ",", 
        RowBox[{"{", 
         RowBox[{"t", ",", "2"}], "}"}]}], "]"}], "2"]}], "-", " ", 
    RowBox[{"2", " ", 
     FractionBox["e", "d"], "  ", 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"t", ",", "4"}], "}"}]}], "]"}], 
     RowBox[{"(", 
      RowBox[{"1", "-", 
       RowBox[{"2", "u"}]}], ")"}]}]}]}], "//", "Simplify"}]}], "Input",
 CellChangeTimes->{{3.612103903513022*^9, 3.612103952230616*^9}, {
   3.612104065523182*^9, 3.612104106479678*^9}, {3.612104142503398*^9, 
   3.612104153775474*^9}, {3.6121042302534924`*^9, 3.612104355871231*^9}, {
   3.6121043889598017`*^9, 3.612104444472445*^9}, {3.6121044760078697`*^9, 
   3.612104503825255*^9}, {3.6121045731902*^9, 3.612104576043758*^9}, {
   3.612104748095953*^9, 3.61210484098662*^9}, {3.612104880027342*^9, 
   3.6121048979854717`*^9}, {3.6121049886695023`*^9, 3.61210505456924*^9}, {
   3.612105173607251*^9, 3.612105219526963*^9}, {3.612105277740992*^9, 
   3.6121053074434433`*^9}, {3.6121053934262466`*^9, 3.612105398686166*^9}, 
   3.612105474655007*^9, {3.612105594734805*^9, 3.612105668590907*^9}, {
   3.612105910056315*^9, 3.6121059859921703`*^9}, {3.612106052116117*^9, 
   3.612106057330433*^9}}],

Cell[BoxData[
 RowBox[{
  FractionBox["1", "2"], " ", 
  RowBox[{"(", 
   RowBox[{"1", "-", 
    RowBox[{"d", " ", 
     RowBox[{"Tanh", "[", 
      RowBox[{"e", " ", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}], "]"}]}]}], 
   ")"}]}]], "Output",
 CellChangeTimes->{
  3.612103956526335*^9, {3.612104079249251*^9, 3.612104107545743*^9}, 
   3.61210415466225*^9, 3.612104235987838*^9, 3.612104267786392*^9, {
   3.6121043104675694`*^9, 3.6121043570816927`*^9}, {3.612104407092023*^9, 
   3.612104504402313*^9}, {3.6121048165527973`*^9, 3.612104841606307*^9}, {
   3.6121048813607073`*^9, 3.612104899058373*^9}, {3.612104991534854*^9, 
   3.6121050560966177`*^9}, {3.61210518691214*^9, 3.612105220406242*^9}, {
   3.6121052816229877`*^9, 3.612105307951325*^9}, 3.612105399664811*^9, 
   3.612105476561449*^9, {3.612105596621785*^9, 3.6121056214434843`*^9}, {
   3.612105655521185*^9, 3.6121056690866137`*^9}, 3.612105987338585*^9, 
   3.612106058693425*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", 
   FractionBox["1", "2"]}], " ", "d", " ", "e", " ", 
  SuperscriptBox[
   RowBox[{"Sech", "[", 
    RowBox[{"e", " ", 
     RowBox[{"(", 
      RowBox[{
       RowBox[{"-", "\[Pi]"}], "+", "t"}], ")"}]}], "]"}], "2"]}]], "Output",
 CellChangeTimes->{
  3.612103956526335*^9, {3.612104079249251*^9, 3.612104107545743*^9}, 
   3.61210415466225*^9, 3.612104235987838*^9, 3.612104267786392*^9, {
   3.6121043104675694`*^9, 3.6121043570816927`*^9}, {3.612104407092023*^9, 
   3.612104504402313*^9}, {3.6121048165527973`*^9, 3.612104841606307*^9}, {
   3.6121048813607073`*^9, 3.612104899058373*^9}, {3.612104991534854*^9, 
   3.6121050560966177`*^9}, {3.61210518691214*^9, 3.612105220406242*^9}, {
   3.6121052816229877`*^9, 3.612105307951325*^9}, 3.612105399664811*^9, 
   3.612105476561449*^9, {3.612105596621785*^9, 3.6121056214434843`*^9}, {
   3.612105655521185*^9, 3.6121056690866137`*^9}, 3.612105987338585*^9, 
   3.6121060586972017`*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.612103956526335*^9, {3.612104079249251*^9, 3.612104107545743*^9}, 
   3.61210415466225*^9, 3.612104235987838*^9, 3.612104267786392*^9, {
   3.6121043104675694`*^9, 3.6121043570816927`*^9}, {3.612104407092023*^9, 
   3.612104504402313*^9}, {3.6121048165527973`*^9, 3.612104841606307*^9}, {
   3.6121048813607073`*^9, 3.612104899058373*^9}, {3.612104991534854*^9, 
   3.6121050560966177`*^9}, {3.61210518691214*^9, 3.612105220406242*^9}, {
   3.6121052816229877`*^9, 3.612105307951325*^9}, 3.612105399664811*^9, 
   3.612105476561449*^9, {3.612105596621785*^9, 3.6121056214434843`*^9}, {
   3.612105655521185*^9, 3.6121056690866137`*^9}, 3.612105987338585*^9, 
   3.612106058700289*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.612103956526335*^9, {3.612104079249251*^9, 3.612104107545743*^9}, 
   3.61210415466225*^9, 3.612104235987838*^9, 3.612104267786392*^9, {
   3.6121043104675694`*^9, 3.6121043570816927`*^9}, {3.612104407092023*^9, 
   3.612104504402313*^9}, {3.6121048165527973`*^9, 3.612104841606307*^9}, {
   3.6121048813607073`*^9, 3.612104899058373*^9}, {3.612104991534854*^9, 
   3.6121050560966177`*^9}, {3.61210518691214*^9, 3.612105220406242*^9}, {
   3.6121052816229877`*^9, 3.612105307951325*^9}, 3.612105399664811*^9, 
   3.612105476561449*^9, {3.612105596621785*^9, 3.6121056214434843`*^9}, {
   3.612105655521185*^9, 3.6121056690866137`*^9}, 3.612105987338585*^9, 
   3.6121060587031937`*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.612103956526335*^9, {3.612104079249251*^9, 3.612104107545743*^9}, 
   3.61210415466225*^9, 3.612104235987838*^9, 3.612104267786392*^9, {
   3.6121043104675694`*^9, 3.6121043570816927`*^9}, {3.612104407092023*^9, 
   3.612104504402313*^9}, {3.6121048165527973`*^9, 3.612104841606307*^9}, {
   3.6121048813607073`*^9, 3.612104899058373*^9}, {3.612104991534854*^9, 
   3.6121050560966177`*^9}, {3.61210518691214*^9, 3.612105220406242*^9}, {
   3.6121052816229877`*^9, 3.612105307951325*^9}, 3.612105399664811*^9, 
   3.612105476561449*^9, {3.612105596621785*^9, 3.6121056214434843`*^9}, {
   3.612105655521185*^9, 3.6121056690866137`*^9}, 3.612105987338585*^9, 
   3.612106058706265*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.612103956526335*^9, {3.612104079249251*^9, 3.612104107545743*^9}, 
   3.61210415466225*^9, 3.612104235987838*^9, 3.612104267786392*^9, {
   3.6121043104675694`*^9, 3.6121043570816927`*^9}, {3.612104407092023*^9, 
   3.612104504402313*^9}, {3.6121048165527973`*^9, 3.612104841606307*^9}, {
   3.6121048813607073`*^9, 3.612104899058373*^9}, {3.612104991534854*^9, 
   3.6121050560966177`*^9}, {3.61210518691214*^9, 3.612105220406242*^9}, {
   3.6121052816229877`*^9, 3.612105307951325*^9}, 3.612105399664811*^9, 
   3.612105476561449*^9, {3.612105596621785*^9, 3.6121056214434843`*^9}, {
   3.612105655521185*^9, 3.6121056690866137`*^9}, 3.612105987338585*^9, 
   3.612106058709219*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"ParametricPlot", "[", 
  RowBox[{
   RowBox[{
    FractionBox["1", "16"], 
    RowBox[{"{", " ", 
     RowBox[{
      RowBox[{"16", 
       SuperscriptBox[
        RowBox[{"Sin", "[", "t", "]"}], "3"]}], ",", 
      RowBox[{
       RowBox[{"13", " ", 
        RowBox[{"Cos", "[", "t", "]"}]}], "-", 
       RowBox[{"5", " ", 
        RowBox[{"Cos", "[", 
         RowBox[{"2", " ", "t"}], "]"}]}], "-", 
       RowBox[{"2", 
        RowBox[{"Cos", "[", 
         RowBox[{"3", "t"}], "]"}]}], "-", 
       RowBox[{"Cos", "[", 
        RowBox[{"4", "t"}], "]"}]}]}], "}"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"t", ",", "0", ",", 
     RowBox[{"2", "\[Pi]"}]}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.612137843113668*^9, 3.6121379633929453`*^9}, {
  3.612138610399036*^9, 3.612138640321391*^9}, {3.612138847446521*^9, 
  3.612138853436541*^9}, {3.612138986280814*^9, 3.612138992199215*^9}}],

Cell[BoxData[
 GraphicsBox[{{}, {}, 
   {Hue[0.67, 0.6, 0.6], LineBox[CompressedData["
1:eJxVm3c81e/7x60ke6S0haRQWsrIRUmpJBJKKCNaqMwyQ/asyCiRbBnZ67Zl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     "]]}},
  Axes->True,
  AxesOrigin->{0, 0},
  Method->{},
  PlotRange->{{-0.9999995778436735, 
   0.9999996348235101}, {-1.0624997735744195`, 0.7452030261987206}},
  PlotRangeClipping->True,
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02]}]], "Output",
 CellChangeTimes->{
  3.6121379652513847`*^9, {3.6121386117698727`*^9, 3.6121386406964912`*^9}, {
   3.61213884827689*^9, 3.612138855153955*^9}, {3.6121389872165937`*^9, 
   3.612138992810112*^9}},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"13", " ", 
    RowBox[{"Cos", "[", "t", "]"}]}], "-", 
   RowBox[{"5", " ", 
    RowBox[{"Cos", "[", 
     RowBox[{"2", " ", "t"}], "]"}]}], "-", 
   RowBox[{"2", 
    RowBox[{"Cos", "[", 
     RowBox[{"3", "t"}], "]"}]}], "-", 
   RowBox[{"Cos", "[", 
    RowBox[{"4", "t"}], "]"}]}], "//", "TrigFactor"}]], "Input",
 CellChangeTimes->{{3.6121380044197607`*^9, 3.6121380115638227`*^9}, {
  3.612138250586157*^9, 3.612138252539819*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"13", " ", 
   RowBox[{"Cos", "[", "t", "]"}]}], "-", 
  RowBox[{"5", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"2", " ", "t"}], "]"}]}], "-", 
  RowBox[{"2", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"3", " ", "t"}], "]"}]}], "-", 
  RowBox[{"Cos", "[", 
   RowBox[{"4", " ", "t"}], "]"}]}]], "Output",
 CellChangeTimes->{{3.612138007016981*^9, 3.612138012266515*^9}, 
   3.612138253245789*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"D", "[", 
  RowBox[{
   FractionBox[
    RowBox[{"f", "[", 
     RowBox[{"r", ",", "t"}], "]"}], 
    RowBox[{" ", 
     RowBox[{"a", "[", 
      RowBox[{"r", ",", "t"}], "]"}]}]], ",", "r"}], "]"}]], "Input",
 CellChangeTimes->{{3.6122872529312773`*^9, 3.612287267405322*^9}, {
  3.61228976740524*^9, 3.61228980191929*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", 
   FractionBox[
    RowBox[{
     RowBox[{"f", "[", 
      RowBox[{"r", ",", "t"}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["a", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"r", ",", "t"}], "]"}]}], 
    SuperscriptBox[
     RowBox[{"a", "[", 
      RowBox[{"r", ",", "t"}], "]"}], "2"]]}], "+", 
  FractionBox[
   RowBox[{
    SuperscriptBox["f", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"r", ",", "t"}], "]"}], 
   RowBox[{"a", "[", 
    RowBox[{"r", ",", "t"}], "]"}]]}]], "Output",
 CellChangeTimes->{
  3.612287267878768*^9, {3.612289783112054*^9, 3.612289803753827*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"x", "=", 
  RowBox[{"f", "*", 
   RowBox[{"Cosh", "[", "n", "]"}], 
   RowBox[{"Cos", "[", "t", "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{"y", "=", 
  RowBox[{"f", "*", 
   RowBox[{"Sinh", "[", "n", "]"}], 
   RowBox[{"Sin", "[", "t", "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"x", ",", 
    RowBox[{"{", 
     RowBox[{"n", ",", "2"}], "}"}]}], "]"}], "\[Equal]", 
  "x"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"y", ",", 
    RowBox[{"{", 
     RowBox[{"n", ",", "2"}], "}"}]}], "]"}], "\[Equal]", "y"}]}], "Input",
 CellChangeTimes->{{3.6123931122780123`*^9, 3.6123931822989397`*^9}}],

Cell[BoxData[
 RowBox[{"f", " ", 
  RowBox[{"Cos", "[", "t", "]"}], " ", 
  RowBox[{"Cosh", "[", "n", "]"}]}]], "Output",
 CellChangeTimes->{{3.612393169399432*^9, 3.612393182678341*^9}}],

Cell[BoxData[
 RowBox[{"f", " ", 
  RowBox[{"Sin", "[", "t", "]"}], " ", 
  RowBox[{"Sinh", "[", "n", "]"}]}]], "Output",
 CellChangeTimes->{{3.612393169399432*^9, 3.612393182686556*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{{3.612393169399432*^9, 3.612393182696794*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{{3.612393169399432*^9, 3.612393182703821*^9}}]
}, Open  ]],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.612287262419858*^9, 3.6122872636126957`*^9}}],

Cell[BoxData[
 FormBox[
  RowBox[{
   FractionBox["1", "s"], 
   FractionBox["1", 
    RowBox[{"1", "\[Minus]", 
     RowBox[{
      SuperscriptBox["e", 
       RowBox[{"T", "s"}]], 
      SuperscriptBox["z", 
       RowBox[{"\[Minus]", "1"}]]}]}]]}], TraditionalForm]], "Input",
 CellChangeTimes->{3.6150362436963987`*^9}],

Cell[BoxData[
 RowBox[{"D", "[", 
  RowBox[{
   RowBox[{
    FractionBox["1", "s"], 
    FractionBox["1", 
     RowBox[{"1", "\[Minus]", 
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"T", "s"}]], 
       SuperscriptBox["z", 
        RowBox[{"\[Minus]", "1"}]]}]}]]}], ",", 
   RowBox[{"{", 
    RowBox[{"s", ",", "2"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.6150362534416513`*^9, 3.615036279053885*^9}}],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   FractionBox["2", 
    RowBox[{
     SuperscriptBox["s", "3"], " ", 
     RowBox[{"(", 
      RowBox[{"1", "-", 
       FractionBox[
        SuperscriptBox["\[ExponentialE]", 
         RowBox[{"s", " ", "T"}]], "z"]}], ")"}]}]], "+", 
   FractionBox[
    RowBox[{
     FractionBox[
      RowBox[{"2", " ", 
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"2", " ", "s", " ", "T"}]], " ", 
       SuperscriptBox["T", "2"]}], 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{"1", "-", 
          FractionBox[
           SuperscriptBox["\[ExponentialE]", 
            RowBox[{"s", " ", "T"}]], "z"]}], ")"}], "3"], " ", 
       SuperscriptBox["z", "2"]}]], "+", 
     FractionBox[
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"s", " ", "T"}]], " ", 
       SuperscriptBox["T", "2"]}], 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{"1", "-", 
          FractionBox[
           SuperscriptBox["\[ExponentialE]", 
            RowBox[{"s", " ", "T"}]], "z"]}], ")"}], "2"], " ", "z"}]]}], 
    "s"], "-", 
   FractionBox[
    RowBox[{"2", " ", 
     SuperscriptBox["\[ExponentialE]", 
      RowBox[{"s", " ", "T"}]], " ", "T"}], 
    RowBox[{
     SuperscriptBox["s", "2"], " ", 
     SuperscriptBox[
      RowBox[{"(", 
       RowBox[{"1", "-", 
        FractionBox[
         SuperscriptBox["\[ExponentialE]", 
          RowBox[{"s", " ", "T"}]], "z"]}], ")"}], "2"], " ", "z"}]]}], "//", 
  "Simplify"}]], "Input",
 CellChangeTimes->{{3.615036420069787*^9, 3.615036424117453*^9}}],

Cell[BoxData[
 RowBox[{"-", 
  FractionBox[
   RowBox[{"z", " ", 
    RowBox[{"(", 
     RowBox[{
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"2", " ", "s", " ", "T"}]], " ", 
       RowBox[{"(", 
        RowBox[{"2", "+", 
         RowBox[{"2", " ", "s", " ", "T"}], "+", 
         RowBox[{
          SuperscriptBox["s", "2"], " ", 
          SuperscriptBox["T", "2"]}]}], ")"}]}], "+", 
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"s", " ", "T"}]], " ", 
       RowBox[{"(", 
        RowBox[{
         RowBox[{"-", "4"}], "-", 
         RowBox[{"2", " ", "s", " ", "T"}], "+", 
         RowBox[{
          SuperscriptBox["s", "2"], " ", 
          SuperscriptBox["T", "2"]}]}], ")"}], " ", "z"}], "+", 
      RowBox[{"2", " ", 
       SuperscriptBox["z", "2"]}]}], ")"}]}], 
   RowBox[{
    SuperscriptBox["s", "3"], " ", 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox["\[ExponentialE]", 
        RowBox[{"s", " ", "T"}]], "-", "z"}], ")"}], "3"]}]]}]], "Output",
 CellChangeTimes->{3.615036425108549*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"u", "=", 
  RowBox[{"e", 
   RowBox[{"(", 
    RowBox[{"5", "+", 
     RowBox[{"Cos", "[", 
      RowBox[{
       RowBox[{"c", " ", "x"}], "+", 
       RowBox[{"d", " ", "y"}]}], "]"}]}], ")"}]}]}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", "y"}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "2"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", "2"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", "x", ",", "y"}], "]"}]}], "Input",
 CellChangeTimes->{{3.615057588945806*^9, 3.615057669018404*^9}, {
  3.6150577646663723`*^9, 3.6150577991509037`*^9}, {3.615058646951198*^9, 
  3.6150586816520967`*^9}}],

Cell[BoxData[
 RowBox[{"e", " ", 
  RowBox[{"(", 
   RowBox[{"5", "+", 
    RowBox[{"Cos", "[", 
     RowBox[{
      RowBox[{"c", " ", "x"}], "+", 
      RowBox[{"d", " ", "y"}]}], "]"}]}], ")"}]}]], "Output",
 CellChangeTimes->{{3.615058650848875*^9, 3.615058683234322*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", "d"}], " ", "e", " ", 
  RowBox[{"Sin", "[", 
   RowBox[{
    RowBox[{"c", " ", "x"}], "+", 
    RowBox[{"d", " ", "y"}]}], "]"}]}]], "Output",
 CellChangeTimes->{{3.615058650848875*^9, 3.615058683236465*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", 
   SuperscriptBox["c", "2"]}], " ", "e", " ", 
  RowBox[{"Cos", "[", 
   RowBox[{
    RowBox[{"c", " ", "x"}], "+", 
    RowBox[{"d", " ", "y"}]}], "]"}]}]], "Output",
 CellChangeTimes->{{3.615058650848875*^9, 3.615058683237974*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", 
   SuperscriptBox["d", "2"]}], " ", "e", " ", 
  RowBox[{"Cos", "[", 
   RowBox[{
    RowBox[{"c", " ", "x"}], "+", 
    RowBox[{"d", " ", "y"}]}], "]"}]}]], "Output",
 CellChangeTimes->{{3.615058650848875*^9, 3.615058683240156*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"-", "c"}], " ", "d", " ", "e", " ", 
  RowBox[{"Cos", "[", 
   RowBox[{
    RowBox[{"c", " ", "x"}], "+", 
    RowBox[{"d", " ", "y"}]}], "]"}]}]], "Output",
 CellChangeTimes->{{3.615058650848875*^9, 3.615058683242097*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"D", "[", 
     RowBox[{
      RowBox[{
       RowBox[{"(", 
        RowBox[{
         RowBox[{"2", " ", 
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}], 
          RowBox[{"d", "[", "x", "]"}], " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", " ", 
         RowBox[{
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{
           SuperscriptBox["c", "\[Prime]\[Prime]",
            MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], "x", " ", 
       RowBox[{"Cos", "[", 
        RowBox[{"x", " ", 
         RowBox[{"c", "[", "y", "]"}]}], "]"}]}], ",", "y"}], "]"}], "+", 
    RowBox[{
     SuperscriptBox["x", "2"], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], "u"}]}], "\[Equal]", 
   RowBox[{
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"x", "  ", 
        RowBox[{
         SuperscriptBox["c", 
          TagBox[
           RowBox[{"(", "3", ")"}],
           Derivative],
          MultilineFunction->None], "[", "y", "]"}]}], "-", 
       RowBox[{"2", " ", "x", "  ", 
        SuperscriptBox[
         RowBox[{"d", "[", "x", "]"}], "2"], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "-", 
    RowBox[{"2", " ", 
     SuperscriptBox["x", "2"], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"d", "[", "x", "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     SuperscriptBox[
      RowBox[{
       SuperscriptBox["c", "\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "2"]}], "+", 
    RowBox[{"3", " ", "x", " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"d", "[", "x", "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "y", "]"}]}]}]}], "//", 
  "Simplify"}]], "Input",
 CellChangeTimes->{{3.615066779168092*^9, 3.6150667834732933`*^9}, 
   3.615066852166809*^9, 3.615066902295072*^9, {3.61506822392966*^9, 
   3.615068228850297*^9}, {3.615068375219747*^9, 3.615068389539063*^9}, {
   3.615068464170476*^9, 3.615068464721846*^9}, 3.615068894935835*^9, {
   3.615069093146647*^9, 3.615069094271327*^9}, {3.615069789294175*^9, 
   3.6150698049331703`*^9}, {3.615069853578573*^9, 3.6150698616625338`*^9}, {
   3.615069934950449*^9, 3.615070024303301*^9}, {3.615070065168003*^9, 
   3.615070099584332*^9}, {3.6150701656850367`*^9, 3.615070235412835*^9}, {
   3.615070512565145*^9, 3.6150705191144733`*^9}, {3.6150706169600697`*^9, 
   3.615070623909513*^9}, {3.615070672027503*^9, 3.6150706985264673`*^9}, {
   3.615070768043292*^9, 3.615070851448985*^9}, {3.6150709008009*^9, 
   3.615070918221874*^9}, {3.615070963785268*^9, 3.615070985035646*^9}, {
   3.6150712625833263`*^9, 3.615071263152144*^9}, {3.6150713018917933`*^9, 
   3.61507132612814*^9}, {3.615071888243146*^9, 3.615071895641925*^9}, {
   3.615071936695321*^9, 3.615072010933419*^9}, {3.6150720784718933`*^9, 
   3.615072080763962*^9}, {3.615072114866661*^9, 3.6150721512001133`*^9}, {
   3.615072249325021*^9, 3.6150723744641237`*^9}, {3.6150728607664423`*^9, 
   3.615072883230667*^9}, {3.615073103064867*^9, 3.615073166388307*^9}, {
   3.615073356405596*^9, 3.6150733680733557`*^9}, {3.615073432533596*^9, 
   3.615073448674646*^9}, {3.61507351254906*^9, 3.615073560800408*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.6150728838808603`*^9, {3.615073109989148*^9, 3.615073134268937*^9}, 
   3.6150735183677263`*^9, 3.6150735615121107`*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"-", "2"}], " ", "x", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   SuperscriptBox[
    RowBox[{"d", "[", "x", "]"}], "2"], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}], "-", 
  RowBox[{"2", " ", 
   SuperscriptBox["x", "2"], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"d", "[", "x", "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   SuperscriptBox[
    RowBox[{
     SuperscriptBox["c", "\[Prime]",
      MultilineFunction->None], "[", "y", "]"}], "2"]}], "+", 
  RowBox[{"3", " ", "x", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"d", "[", "x", "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}], "-", 
  RowBox[{
   SuperscriptBox["x", "2"], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}], "+", 
  RowBox[{"x", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", 
     TagBox[
      RowBox[{"(", "3", ")"}],
      Derivative],
     MultilineFunction->None], "[", "y", "]"}]}]}]], "Input"],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", "x", ",", "y"}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"x", " ", 
         RowBox[{"c", "[", "y", "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "u"}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{
        RowBox[{"c", "[", "y", "]"}], " ", 
        RowBox[{"d", "[", "x", "]"}]}], "+", 
       RowBox[{"x", " ", "y", "  ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}]}], "+", 
    RowBox[{
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], "  ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}]}]}]}], "//", "FullSimplify"}]
  ], "Input",
 CellChangeTimes->{{3.615069462993784*^9, 3.6150696030642967`*^9}, {
  3.61506964976482*^9, 3.6150697865742807`*^9}, {3.6150760730413837`*^9, 
  3.615076110502449*^9}, {3.615076176654965*^9, 3.6150761942825527`*^9}, {
  3.615076287271418*^9, 3.6150763789765787`*^9}, {3.61507645183501*^9, 
  3.6150764737099648`*^9}}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.6150760737280407`*^9, 3.6150761113379374`*^9, {3.615076195223977*^9, 
   3.615076200483067*^9}, {3.615076291562766*^9, 3.615076339080614*^9}, 
   3.615076381474655*^9, 3.615076474649703*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"c", "[", "y", "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"d", "[", "x", "]"}]}], "+", 
  RowBox[{
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}], "-", 
  RowBox[{"x", " ", 
   RowBox[{"c", "[", "y", "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}], "+", 
  RowBox[{
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["d", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}], "-", 
  RowBox[{"y", " ", 
   RowBox[{"d", "[", "x", "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["d", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}], "+", 
  RowBox[{"x", " ", "y", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}], " ", 
   RowBox[{
    SuperscriptBox["d", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}]}]], "Input"],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"u", "=", 
  RowBox[{
   RowBox[{"Sin", "[", 
    RowBox[{
     RowBox[{"c", "[", "y", "]"}], "x"}], "]"}], 
   RowBox[{"Sin", "[", 
    RowBox[{
     RowBox[{"d", "[", "x", "]"}], "y"}], "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", "1"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{"u", ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", "1"}], "}"}]}], "]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", "x", ",", "y"}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"x", " ", 
         RowBox[{"c", "[", "y", "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "u"}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{
        RowBox[{"c", "[", "y", "]"}], " ", 
        RowBox[{"d", "[", "x", "]"}]}], "+", 
       RowBox[{"x", " ", "y", "  ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}]}], "+", 
    RowBox[{
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], "  ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}]}]}]}], "//", 
  "FullSimplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "2"}], "}"}]}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", 
      RowBox[{"(", 
       RowBox[{
        SuperscriptBox[
         RowBox[{"c", "[", "y", "]"}], "2"], " ", "+", 
        RowBox[{
         SuperscriptBox["y", "2"], " ", 
         SuperscriptBox[
          RowBox[{
           SuperscriptBox["d", "\[Prime]",
            MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}]}], 
     "u"}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"2", "  ", 
        RowBox[{"c", "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}], 
        RowBox[{"Cos", "[", 
         RowBox[{"x", " ", 
          RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
       RowBox[{
        RowBox[{"Sin", "[", 
         RowBox[{"x", " ", 
          RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], "y", " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"y", ",", "2"}], "}"}]}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", 
      RowBox[{"(", 
       RowBox[{
        SuperscriptBox[
         RowBox[{"d", "[", "x", "]"}], "2"], " ", "+", 
        RowBox[{
         SuperscriptBox["x", "2"], " ", 
         SuperscriptBox[
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}], "2"]}]}], ")"}]}], 
     "u"}], "+", " ", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"2", " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], 
        RowBox[{"d", "[", "x", "]"}], " ", 
        RowBox[{"Cos", "[", 
         RowBox[{"y", " ", 
          RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", " ", 
       RowBox[{
        RowBox[{"Sin", "[", 
         RowBox[{"y", " ", 
          RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]\[Prime]",
          MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], "x", " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}]}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "2"}], "}"}], ",", "y"}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"2", " ", 
         RowBox[{"c", "[", "y", "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}], "+", 
        RowBox[{"2", " ", "y", " ", 
         SuperscriptBox[
          RowBox[{
           SuperscriptBox["d", "\[Prime]",
            MultilineFunction->None], "[", "x", "]"}], "2"]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "u"}], "-", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"c", "[", "y", "]"}], "2"], " ", "+", 
       RowBox[{
        SuperscriptBox["y", "2"], " ", 
        SuperscriptBox[
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"y", ",", "1"}], "}"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"2", " ", 
        RowBox[{"c", "[", "y", "]"}], "  ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}], "+", 
       RowBox[{"2", " ", "y", "  ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}], "+", 
       RowBox[{"x", " ", "y", " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], " ", "+", 
    RowBox[{
     RowBox[{"(", " ", 
      RowBox[{
       RowBox[{
        SuperscriptBox["d", "\[Prime]\[Prime]",
         MultilineFunction->None], "[", "x", "]"}], "-", 
       RowBox[{"2", " ", "x", " ", "y", " ", 
        RowBox[{"c", "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "-", 
    RowBox[{"2", " ", "y", " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"d", "[", "x", "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}]}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"y", ",", "2"}], "}"}], ",", "x"}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"2", "x", " ", 
         SuperscriptBox[
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}], "2"]}], "+", 
        RowBox[{"2", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}], "+", 
        RowBox[{"x", " ", 
         RowBox[{"c", "[", "y", "]"}], 
         RowBox[{
          SuperscriptBox["c", "\[Prime]\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}], "u"}], "-", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"d", "[", "x", "]"}], "2"], " ", "+", 
       RowBox[{
        SuperscriptBox["x", "2"], " ", 
        SuperscriptBox[
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}], "2"]}]}], ")"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "1"}], "}"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"2", " ", 
        RowBox[{"d", "[", "x", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}]}], "+", 
       RowBox[{"2", " ", "x", " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}], "+", 
       RowBox[{"x", " ", "y", "  ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]\[Prime]",
          MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", " ", 
      RowBox[{
       RowBox[{
        SuperscriptBox["c", "\[Prime]\[Prime]",
         MultilineFunction->None], "[", "y", "]"}], "-", 
       RowBox[{"2", " ", "x", " ", "y", " ", 
        RowBox[{"d", "[", "x", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "-", 
    RowBox[{"2", " ", "x", " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], 
     RowBox[{"d", "[", "x", "]"}], 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"x", ",", "3"}], "}"}]}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", "3"}], 
     SuperscriptBox["y", "2"], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "x", "]"}], "u"}], "-", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"c", "[", "y", "]"}], "2"], " ", "+", 
       RowBox[{
        SuperscriptBox["y", "2"], " ", 
        SuperscriptBox[
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "1"}], "}"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"y", "  ", 
        RowBox[{
         SuperscriptBox["d", 
          TagBox[
           RowBox[{"(", "3", ")"}],
           Derivative],
          MultilineFunction->None], "[", "x", "]"}]}], "-", 
       RowBox[{"2", " ", "y", " ", 
        SuperscriptBox[
         RowBox[{"c", "[", "y", "]"}], "2"], "  ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
    RowBox[{"3", " ", "y", " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "x", "]"}]}], "-", 
    RowBox[{"2", " ", 
     SuperscriptBox["y", "2"], " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     SuperscriptBox[
      RowBox[{
       SuperscriptBox["d", "\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "2"]}]}]}], "//", 
  "Simplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{"u", ",", 
     RowBox[{"{", 
      RowBox[{"y", ",", "3"}], "}"}]}], "]"}], "==", 
   RowBox[{
    RowBox[{
     RowBox[{"-", "3"}], 
     SuperscriptBox["x", "2"], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], "u"}], "-", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"d", "[", "x", "]"}], "2"], " ", "+", 
       RowBox[{
        SuperscriptBox["x", "2"], " ", 
        SuperscriptBox[
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}], "2"]}]}], ")"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"y", ",", "1"}], "}"}]}], "]"}]}], "+", " ", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"x", "  ", 
        RowBox[{
         SuperscriptBox["c", 
          TagBox[
           RowBox[{"(", "3", ")"}],
           Derivative],
          MultilineFunction->None], "[", "y", "]"}]}], "-", 
       RowBox[{"2", " ", "x", "  ", 
        SuperscriptBox[
         RowBox[{"d", "[", "x", "]"}], "2"], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "-", 
    RowBox[{"2", " ", 
     SuperscriptBox["x", "2"], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"d", "[", "x", "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     SuperscriptBox[
      RowBox[{
       SuperscriptBox["c", "\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "2"]}], "+", 
    RowBox[{"3", " ", "x", " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"d", "[", "x", "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "y", "]"}]}]}]}], "//", 
  "Simplify"}]}], "Input",
 CellChangeTimes->{{3.615062137030911*^9, 3.615062169244606*^9}, {
   3.615062934723803*^9, 3.615062944525571*^9}, {3.615063258862752*^9, 
   3.615063273212738*^9}, {3.615063305143128*^9, 3.615063354454322*^9}, {
   3.615063398625304*^9, 3.615063436439501*^9}, {3.615063482534436*^9, 
   3.615063531366317*^9}, {3.615063561909669*^9, 3.615063620251918*^9}, {
   3.615063660818438*^9, 3.615063694465962*^9}, {3.615063765025031*^9, 
   3.615063815520048*^9}, {3.615063851765964*^9, 3.615063860227251*^9}, {
   3.615066140790427*^9, 3.6150661843156633`*^9}, {3.6150664012341833`*^9, 
   3.615066413411311*^9}, 3.6150665547822733`*^9, {3.615066751913068*^9, 
   3.6150667629042*^9}, {3.6150667967025414`*^9, 3.6150668679403*^9}, {
   3.615066920622025*^9, 3.61506693093734*^9}, {3.615067050353058*^9, 
   3.615067072736525*^9}, {3.6150675520420513`*^9, 3.615067612967153*^9}, {
   3.61506819211791*^9, 3.61506819664608*^9}, {3.6150703953363237`*^9, 
   3.6150705049793377`*^9}, 3.6150705907616873`*^9, {3.615070733666098*^9, 
   3.615070736949379*^9}, 3.615071391952183*^9, {3.615071433201776*^9, 
   3.615071479591724*^9}, {3.615071569571816*^9, 3.6150715789427013`*^9}, 
   3.615071751581129*^9, {3.615071835673768*^9, 3.615071876099642*^9}, 
   3.6150719136289883`*^9, {3.615072027904003*^9, 3.615072028356015*^9}, {
   3.615072805557415*^9, 3.61507284807012*^9}, 3.615072906348316*^9, {
   3.615072976233551*^9, 3.615073023263844*^9}, {3.615073460058543*^9, 
   3.6150734728521748`*^9}, {3.615073584440321*^9, 3.615073592787531*^9}, {
   3.6150760495508137`*^9, 3.615076069331298*^9}, {3.615076690863405*^9, 
   3.6150766917772627`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{"Sin", "[", 
   RowBox[{"x", " ", 
    RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
  RowBox[{"Sin", "[", 
   RowBox[{"y", " ", 
    RowBox[{"d", "[", "x", "]"}]}], "]"}]}]], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076057776702*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"c", "[", "y", "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
  RowBox[{"y", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["d", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076057783996*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"d", "[", "x", "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
  RowBox[{"x", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076057789336*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"c", "[", "y", "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"d", "[", "x", "]"}]}], "+", 
  RowBox[{
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}], "-", 
  RowBox[{"x", " ", 
   RowBox[{"c", "[", "y", "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}]}], "+", 
  RowBox[{
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["d", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}], "-", 
  RowBox[{"y", " ", 
   RowBox[{"d", "[", "x", "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["d", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}], "+", 
  RowBox[{"x", " ", "y", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"x", " ", 
     RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"y", " ", 
     RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["c", "\[Prime]",
     MultilineFunction->None], "[", "y", "]"}], " ", 
   RowBox[{
    SuperscriptBox["d", "\[Prime]",
     MultilineFunction->None], "[", "x", "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076057794868*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076057984898*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076058225637*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.6150760599064083`*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076061445912*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.6150760617675056`*^9}],

Cell[BoxData["True"], "Output",
 CellChangeTimes->{
  3.615062171672811*^9, 3.615062946192276*^9, {3.615063262402973*^9, 
   3.615063274488916*^9}, {3.615063316408147*^9, 3.615063355303054*^9}, 
   3.615063402912786*^9, 3.615063438087174*^9, {3.615063488684784*^9, 
   3.6150635807673607`*^9}, 3.61506362184943*^9, {3.615063666489374*^9, 
   3.615063694969111*^9}, 3.6150637706912727`*^9, 3.615063833661091*^9, 
   3.615066303503079*^9, 3.615066415236904*^9, 3.615066869371471*^9, {
   3.6150669237722816`*^9, 3.6150669323859043`*^9}, {3.615067059491522*^9, 
   3.615067074115354*^9}, {3.615067561019772*^9, 3.615067614037587*^9}, 
   3.615068198332047*^9, 3.615070407455776*^9, 3.615071393614255*^9, {
   3.615071436035019*^9, 3.615071480237071*^9}, 3.615071579517425*^9, 
   3.615072807349246*^9, {3.61507297691035*^9, 3.6150730250536327`*^9}, 
   3.615073593889146*^9, 3.615076062086224*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"D", "[", 
  RowBox[{
   RowBox[{"u", "[", 
    RowBox[{"x", ",", "y"}], "]"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", "1"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.615074659438265*^9, 3.615074683612134*^9}}],

Cell[BoxData[
 RowBox[{
  SuperscriptBox["u", 
   TagBox[
    RowBox[{"(", 
     RowBox[{"0", ",", "1"}], ")"}],
    Derivative],
   MultilineFunction->None], "[", 
  RowBox[{"x", ",", "y"}], "]"}]], "Output",
 CellChangeTimes->{{3.61507467414998*^9, 3.6150746840663548`*^9}}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{
     RowBox[{"-", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"x", " ", 
         RowBox[{"c", "[", "y", "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "u"}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{
        RowBox[{"c", "[", "y", "]"}], " ", 
        RowBox[{"d", "[", "x", "]"}]}], "+", 
       RowBox[{"x", " ", "y", "  ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}]}], "+", 
    RowBox[{
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], "  ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}]}]}], "/.", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"c", "[", "y", "]"}], "\[Rule]", "c"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["c", "\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dx"}], ",", 
     RowBox[{
      RowBox[{"d", "[", "x", "]"}], "\[Rule]", "d"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dxx"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["u", 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uy"}]}], "}"}]}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{
     RowBox[{"-", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"2", " ", 
         RowBox[{"c", "[", "y", "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}], "+", 
        RowBox[{"2", " ", "y", " ", 
         SuperscriptBox[
          RowBox[{
           SuperscriptBox["d", "\[Prime]",
            MultilineFunction->None], "[", "x", "]"}], "2"]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "u"}], "-", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"c", "[", "y", "]"}], "2"], " ", "+", 
       RowBox[{
        SuperscriptBox["y", "2"], " ", 
        SuperscriptBox[
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}], 
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"2", " ", 
        RowBox[{"c", "[", "y", "]"}], "  ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}], "+", 
       RowBox[{"2", " ", "y", "  ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}], "+", 
       RowBox[{"x", " ", "y", " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], " ", "+", 
    RowBox[{
     RowBox[{"(", " ", 
      RowBox[{
       RowBox[{
        SuperscriptBox["d", "\[Prime]\[Prime]",
         MultilineFunction->None], "[", "x", "]"}], "-", 
       RowBox[{"2", " ", "x", " ", "y", " ", 
        RowBox[{"c", "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "-", 
    RowBox[{"2", " ", "y", " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"d", "[", "x", "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}]}]}], "/.", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"c", "[", "y", "]"}], "\[Rule]", "c"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["c", "\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dx"}], ",", 
     RowBox[{
      RowBox[{"d", "[", "x", "]"}], "\[Rule]", "d"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dxx"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["u", 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uy"}]}], "}"}]}], 
  "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{
     RowBox[{"-", " ", 
      RowBox[{"(", 
       RowBox[{
        RowBox[{"2", "x", " ", 
         SuperscriptBox[
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}], "2"]}], "+", 
        RowBox[{"2", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}], "+", 
        RowBox[{"x", " ", 
         RowBox[{"c", "[", "y", "]"}], 
         RowBox[{
          SuperscriptBox["c", "\[Prime]\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}], "u"}], "-", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"d", "[", "x", "]"}], "2"], " ", "+", 
       RowBox[{
        SuperscriptBox["x", "2"], " ", 
        SuperscriptBox[
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}], "2"]}]}], ")"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "1"}], "}"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"2", " ", 
        RowBox[{"d", "[", "x", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}]}], "+", 
       RowBox[{"2", " ", "x", " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}], "+", 
       RowBox[{"x", " ", "y", "  ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]\[Prime]",
          MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", " ", 
      RowBox[{
       RowBox[{
        SuperscriptBox["c", "\[Prime]\[Prime]",
         MultilineFunction->None], "[", "y", "]"}], "-", 
       RowBox[{"2", " ", "x", " ", "y", " ", 
        RowBox[{"d", "[", "x", "]"}], " ", 
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], " ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "-", 
    RowBox[{"2", " ", "x", " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], 
     RowBox[{"d", "[", "x", "]"}], 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}]}]}], "/.", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"c", "[", "y", "]"}], "\[Rule]", "c"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["c", "\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dx"}], ",", 
     RowBox[{
      RowBox[{"d", "[", "x", "]"}], "\[Rule]", "d"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dxx"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["u", 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["c", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cyy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "dyy"}]}], 
    "}"}]}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{
     RowBox[{"-", "3"}], 
     SuperscriptBox["y", "2"], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "x", "]"}], "u"}], "-", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"c", "[", "y", "]"}], "2"], " ", "+", 
       RowBox[{
        SuperscriptBox["y", "2"], " ", 
        SuperscriptBox[
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}], 
     RowBox[{"D", "[", 
      RowBox[{"u", ",", 
       RowBox[{"{", 
        RowBox[{"x", ",", "1"}], "}"}]}], "]"}]}], "+", 
    RowBox[{
     RowBox[{"(", 
      RowBox[{
       RowBox[{"y", "  ", 
        RowBox[{
         SuperscriptBox["d", 
          TagBox[
           RowBox[{"(", "3", ")"}],
           Derivative],
          MultilineFunction->None], "[", "x", "]"}]}], "-", 
       RowBox[{"2", " ", "y", " ", 
        SuperscriptBox[
         RowBox[{"c", "[", "y", "]"}], "2"], "  ", 
        RowBox[{
         SuperscriptBox["d", "\[Prime]",
          MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
    RowBox[{"3", " ", "y", " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     RowBox[{
      SuperscriptBox["d", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "x", "]"}]}], "-", 
    RowBox[{"2", " ", 
     SuperscriptBox["y", "2"], " ", 
     RowBox[{"c", "[", "y", "]"}], " ", 
     RowBox[{"Cos", "[", 
      RowBox[{"x", " ", 
       RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
     RowBox[{"Sin", "[", 
      RowBox[{"y", " ", 
       RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
     SuperscriptBox[
      RowBox[{
       SuperscriptBox["d", "\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "2"]}]}], "/.", 
   RowBox[{"{", 
    RowBox[{
     RowBox[{
      RowBox[{"c", "[", "y", "]"}], "\[Rule]", "c"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["c", "\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dx"}], ",", 
     RowBox[{
      RowBox[{"d", "[", "x", "]"}], "\[Rule]", "d"}], ",", " ", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dxx"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["u", 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["c", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cyy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", "\[Prime]\[Prime]",
        MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "dyy"}], ",", 
     RowBox[{
      RowBox[{
       SuperscriptBox["d", 
        TagBox[
         RowBox[{"(", "3", ")"}],
         Derivative],
        MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "d3x"}]}], 
    "}"}]}], "\[IndentingNewLine]"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{
   RowBox[{
    RowBox[{"-", "3"}], 
    SuperscriptBox["x", "2"], " ", 
    RowBox[{
     SuperscriptBox["c", "\[Prime]",
      MultilineFunction->None], "[", "y", "]"}], " ", 
    RowBox[{
     SuperscriptBox["c", "\[Prime]\[Prime]",
      MultilineFunction->None], "[", "y", "]"}], "u"}], "-", 
   RowBox[{
    RowBox[{"(", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"d", "[", "x", "]"}], "2"], " ", "+", 
      RowBox[{
       SuperscriptBox["x", "2"], " ", 
       SuperscriptBox[
        RowBox[{
         SuperscriptBox["c", "\[Prime]",
          MultilineFunction->None], "[", "y", "]"}], "2"]}]}], ")"}], 
    RowBox[{"D", "[", 
     RowBox[{"u", ",", 
      RowBox[{"{", 
       RowBox[{"y", ",", "1"}], "}"}]}], "]"}]}], "+", " ", 
   RowBox[{
    RowBox[{"(", 
     RowBox[{
      RowBox[{"x", "  ", 
       RowBox[{
        SuperscriptBox["c", 
         TagBox[
          RowBox[{"(", "3", ")"}],
          Derivative],
         MultilineFunction->None], "[", "y", "]"}]}], "-", 
      RowBox[{"2", " ", "x", "  ", 
       SuperscriptBox[
        RowBox[{"d", "[", "x", "]"}], "2"], " ", 
       RowBox[{
        SuperscriptBox["c", "\[Prime]",
         MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
    RowBox[{"Cos", "[", 
     RowBox[{"x", " ", 
      RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
    RowBox[{"Sin", "[", 
     RowBox[{"y", " ", 
      RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "-", 
   RowBox[{"2", " ", 
    SuperscriptBox["x", "2"], " ", 
    RowBox[{"Cos", "[", 
     RowBox[{"y", " ", 
      RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
    RowBox[{"d", "[", "x", "]"}], " ", 
    RowBox[{"Sin", "[", 
     RowBox[{"x", " ", 
      RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
    SuperscriptBox[
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], "2"]}], "+", 
   RowBox[{"3", " ", "x", " ", 
    RowBox[{"Cos", "[", 
     RowBox[{"x", " ", 
      RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
    RowBox[{"Cos", "[", 
     RowBox[{"y", " ", 
      RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
    RowBox[{"d", "[", "x", "]"}], " ", 
    RowBox[{
     SuperscriptBox["c", "\[Prime]\[Prime]",
      MultilineFunction->None], "[", "y", "]"}]}]}], "/.", 
  RowBox[{"{", 
   RowBox[{
    RowBox[{
     RowBox[{"c", "[", "y", "]"}], "\[Rule]", "c"}], ",", " ", 
    RowBox[{
     RowBox[{
      SuperscriptBox["c", "\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["d", "\[Prime]",
       MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dx"}], ",", 
    RowBox[{
     RowBox[{"d", "[", "x", "]"}], "\[Rule]", "d"}], ",", " ", 
    RowBox[{
     RowBox[{
      SuperscriptBox["d", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "dxx"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["c", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "cyy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["d", "\[Prime]\[Prime]",
       MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "dyy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["d", 
       TagBox[
        RowBox[{"(", "3", ")"}],
        Derivative],
       MultilineFunction->None], "[", "x", "]"}], "\[Rule]", "d3x"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["c", 
       TagBox[
        RowBox[{"(", "3", ")"}],
        Derivative],
       MultilineFunction->None], "[", "y", "]"}], "\[Rule]", "c3y"}]}], 
   "}"}]}]}], "Input",
 CellChangeTimes->{{3.615074542798719*^9, 3.615074648611047*^9}, {
  3.6150746968758507`*^9, 3.615074718179328*^9}, {3.615075060921652*^9, 
  3.6150750797418003`*^9}, {3.615075351196663*^9, 3.615075411859705*^9}, {
  3.615075446945681*^9, 3.615075452019109*^9}, {3.615075769522162*^9, 
  3.615075816125846*^9}, {3.615076702317911*^9, 3.6150767109276543`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{"c", " ", "d"}], "+", 
     RowBox[{"cy", " ", "dx", " ", "x", " ", "y"}]}], ")"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "+", 
  RowBox[{"dx", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}]}], "+", 
  RowBox[{"cy", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"-", "c"}], " ", "cy", " ", "x"}], "-", 
     RowBox[{"d", " ", "dx", " ", "y"}]}], ")"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.6150747201074677`*^9, 3.615075080690811*^9, 3.615075413894512*^9, 
   3.6150754561174383`*^9, {3.615075801507599*^9, 3.615075816631021*^9}, 
   3.6150767130872583`*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"-", "uy"}], " ", 
   RowBox[{"(", 
    RowBox[{
     SuperscriptBox["c", "2"], "+", 
     RowBox[{
      SuperscriptBox["dx", "2"], " ", 
      SuperscriptBox["y", "2"]}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{"2", " ", "c", " ", "dx"}], "+", 
     RowBox[{"2", " ", "cy", " ", "dx", " ", "y"}], "+", 
     RowBox[{"cy", " ", "dxx", " ", "x", " ", "y"}]}], ")"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{"dxx", "-", 
     RowBox[{"2", " ", "c", " ", "cy", " ", "dx", " ", "x", " ", "y"}]}], 
    ")"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}]}], "-", 
  RowBox[{"2", " ", "c", " ", "d", " ", "dx", " ", "y", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"-", "2"}], " ", "c", " ", "cy"}], "-", 
     RowBox[{"2", " ", 
      SuperscriptBox["dx", "2"], " ", "y"}], "-", 
     RowBox[{"d", " ", "dxx", " ", "y"}]}], ")"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}]}]], "Output",
 CellChangeTimes->{
  3.6150747201074677`*^9, 3.615075080690811*^9, 3.615075413894512*^9, 
   3.6150754561174383`*^9, {3.615075801507599*^9, 3.615075816631021*^9}, 
   3.615076713092757*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{"2", " ", "cy", " ", "d"}], "+", 
     RowBox[{"2", " ", "cy", " ", "dx", " ", "x"}], "+", 
     RowBox[{"cyy", " ", "dx", " ", "x", " ", "y"}]}], ")"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "-", 
  RowBox[{"2", " ", "c", " ", "cy", " ", "d", " ", "x", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{"cyy", "-", 
     RowBox[{"2", " ", "cy", " ", "d", " ", "dx", " ", "x", " ", "y"}]}], 
    ")"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      RowBox[{"-", "2"}], " ", "d", " ", "dx"}], "-", 
     RowBox[{"2", " ", 
      SuperscriptBox["cy", "2"], " ", "x"}], "-", 
     RowBox[{"c", " ", "cyy", " ", "x"}]}], ")"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "-", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     SuperscriptBox["d", "2"], "+", 
     RowBox[{
      SuperscriptBox["cy", "2"], " ", 
      SuperscriptBox["x", "2"]}]}], ")"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"dx", " ", "y", " ", 
      RowBox[{"Cos", "[", 
       RowBox[{"d", " ", "y"}], "]"}], " ", 
      RowBox[{"Sin", "[", 
       RowBox[{"c", " ", "x"}], "]"}]}], "+", 
     RowBox[{"c", " ", 
      RowBox[{"Cos", "[", 
       RowBox[{"c", " ", "x"}], "]"}], " ", 
      RowBox[{"Sin", "[", 
       RowBox[{"d", " ", "y"}], "]"}]}]}], ")"}]}]}]], "Output",
 CellChangeTimes->{
  3.6150747201074677`*^9, 3.615075080690811*^9, 3.615075413894512*^9, 
   3.6150754561174383`*^9, {3.615075801507599*^9, 3.615075816631021*^9}, 
   3.615076713097683*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"3", " ", "c", " ", "dxx", " ", "y", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{"d3x", " ", "y"}], "-", 
     RowBox[{"2", " ", 
      SuperscriptBox["c", "2"], " ", "dx", " ", "y"}]}], ")"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}]}], "-", 
  RowBox[{"2", " ", "c", " ", 
   SuperscriptBox["dx", "2"], " ", 
   SuperscriptBox["y", "2"], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "-", 
  RowBox[{"3", " ", "dx", " ", "dxx", " ", 
   SuperscriptBox["y", "2"], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "-", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     SuperscriptBox["c", "2"], "+", 
     RowBox[{
      SuperscriptBox["dx", "2"], " ", 
      SuperscriptBox["y", "2"]}]}], ")"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"dx", " ", "y", " ", 
      RowBox[{"Cos", "[", 
       RowBox[{"d", " ", "y"}], "]"}], " ", 
      RowBox[{"Sin", "[", 
       RowBox[{"c", " ", "x"}], "]"}]}], "+", 
     RowBox[{"c", " ", 
      RowBox[{"Cos", "[", 
       RowBox[{"c", " ", "x"}], "]"}], " ", 
      RowBox[{"Sin", "[", 
       RowBox[{"d", " ", "y"}], "]"}]}]}], ")"}]}]}]], "Output",
 CellChangeTimes->{
  3.6150747201074677`*^9, 3.615075080690811*^9, 3.615075413894512*^9, 
   3.6150754561174383`*^9, {3.615075801507599*^9, 3.615075816631021*^9}, 
   3.6150767131015997`*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"3", " ", "cyy", " ", "d", " ", "x", " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "-", 
  RowBox[{"2", " ", 
   SuperscriptBox["cy", "2"], " ", "d", " ", 
   SuperscriptBox["x", "2"], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"d", " ", "y"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     RowBox[{"c3y", " ", "x"}], "-", 
     RowBox[{"2", " ", "cy", " ", 
      SuperscriptBox["d", "2"], " ", "x"}]}], ")"}], " ", 
   RowBox[{"Cos", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "-", 
  RowBox[{"3", " ", "cy", " ", "cyy", " ", 
   SuperscriptBox["x", "2"], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"c", " ", "x"}], "]"}], " ", 
   RowBox[{"Sin", "[", 
    RowBox[{"d", " ", "y"}], "]"}]}], "-", 
  RowBox[{
   RowBox[{"(", 
    RowBox[{
     SuperscriptBox["d", "2"], "+", 
     RowBox[{
      SuperscriptBox["cy", "2"], " ", 
      SuperscriptBox["x", "2"]}]}], ")"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"d", " ", 
      RowBox[{"Cos", "[", 
       RowBox[{"d", " ", "y"}], "]"}], " ", 
      RowBox[{"Sin", "[", 
       RowBox[{"c", " ", "x"}], "]"}]}], "+", 
     RowBox[{"cy", " ", "x", " ", 
      RowBox[{"Cos", "[", 
       RowBox[{"c", " ", "x"}], "]"}], " ", 
      RowBox[{"Sin", "[", 
       RowBox[{"d", " ", "y"}], "]"}]}]}], ")"}]}]}]], "Output",
 CellChangeTimes->{
  3.6150747201074677`*^9, 3.615075080690811*^9, 3.615075413894512*^9, 
   3.6150754561174383`*^9, {3.615075801507599*^9, 3.615075816631021*^9}, 
   3.615076713105246*^9}]
}, Open  ]],

Cell[BoxData[
 RowBox[{"u", "=."}]], "Input",
 CellChangeTimes->{{3.615062680725999*^9, 3.615062760249062*^9}, {
  3.6150646852794933`*^9, 3.615064686357562*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"D", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"a", "[", 
     RowBox[{"x", ",", "y"}], "]"}], 
    RowBox[{"D", "[", 
     RowBox[{
      RowBox[{"u", "[", 
       RowBox[{"x", ",", "y"}], "]"}], ",", "x"}], "]"}]}], ",", "x"}], 
  "]"}], "\[IndentingNewLine]", 
 RowBox[{"D", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"b", "[", 
     RowBox[{"x", ",", "y"}], "]"}], 
    RowBox[{"D", "[", 
     RowBox[{
      RowBox[{"u", "[", 
       RowBox[{"x", ",", "y"}], "]"}], ",", "y"}], "]"}]}], ",", "y"}], 
  "]"}]}], "Input",
 CellChangeTimes->{{3.615062611013672*^9, 3.6150626703836184`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{
    SuperscriptBox["a", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"a", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"2", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}]}]], "Output",
 CellChangeTimes->{{3.6150626724875383`*^9, 3.615062686289946*^9}, 
   3.615062729909658*^9, 3.615062773229699*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{
    SuperscriptBox["b", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"b", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "2"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}]}]], "Output",
 CellChangeTimes->{{3.6150626724875383`*^9, 3.615062686289946*^9}, 
   3.615062729909658*^9, 3.615062773231978*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"F", "=", 
  RowBox[{
   RowBox[{"D", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"a", "[", 
       RowBox[{"x", ",", "y"}], "]"}], 
      RowBox[{"D", "[", 
       RowBox[{
        RowBox[{"u", "[", 
         RowBox[{"x", ",", "y"}], "]"}], ",", "x"}], "]"}]}], ",", "x"}], 
    "]"}], "+", 
   RowBox[{"D", "[", 
    RowBox[{
     RowBox[{
      RowBox[{"b", "[", 
       RowBox[{"x", ",", "y"}], "]"}], 
      RowBox[{"D", "[", 
       RowBox[{
        RowBox[{"u", "[", 
         RowBox[{"x", ",", "y"}], "]"}], ",", "y"}], "]"}]}], ",", "y"}], 
    "]"}]}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"F", ",", "x"}], "]"}], "/.", 
  RowBox[{"{", 
   RowBox[{
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], " ", "\[Rule]", "uyy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["b", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "bx"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["b", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "by"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["b", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "bxy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uxy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uxyy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["a", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "ax"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uxx"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], " ", "\[Rule]", "ux"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["a", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "axx"}], ",", 
    RowBox[{
     RowBox[{"a", "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "a"}], ",", " ", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"3", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "u3x"}], ",", 
    RowBox[{
     RowBox[{"b", "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "b"}]}], 
   "}"}]}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"F", ",", "y"}], "]"}], "/.", 
  RowBox[{"{", 
   RowBox[{
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], " ", "\[Rule]", "uyy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["b", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "bx"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["b", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "by"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["b", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "bxy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uxy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uxyy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["a", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "ax"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uxx"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], " ", "\[Rule]", "ux"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["a", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "axx"}], ",", 
    RowBox[{
     RowBox[{"a", "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "a"}], ",", " ", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"3", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "u3x"}], ",", 
    RowBox[{
     RowBox[{"b", "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "b"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["a", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "ay"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["b", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "byy"}], ",", " ", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "3"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "u3y"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["a", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "axy"}], ",", 
    RowBox[{
     RowBox[{
      SuperscriptBox["u", 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "\[Rule]", "uxxy"}]}], 
   "}"}]}]}], "Input",
 CellChangeTimes->{{3.6150645610823393`*^9, 3.6150645736267242`*^9}, {
  3.615064608568396*^9, 3.615064666229063*^9}, {3.6150649074065847`*^9, 
  3.6150650257128963`*^9}, {3.615065055747176*^9, 3.615065083532975*^9}, {
  3.6150653311717863`*^9, 3.615065415255127*^9}, {3.61506544669389*^9, 
  3.6150655185989647`*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{
    SuperscriptBox["b", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"b", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "2"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{
    SuperscriptBox["a", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}], "+", 
  RowBox[{
   RowBox[{"a", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{
    SuperscriptBox["u", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"2", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}]}]}]], "Output",
 CellChangeTimes->{{3.615064666647613*^9, 3.6150646911137342`*^9}, {
   3.615065335756137*^9, 3.6150654165344963`*^9}, {3.615065491388652*^9, 
   3.6150655207361593`*^9}, 3.615065633817974*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"a", " ", "u3x"}], "+", 
  RowBox[{"axx", " ", "ux"}], "+", 
  RowBox[{"2", " ", "ax", " ", "uxx"}], "+", 
  RowBox[{"by", " ", "uxy"}], "+", 
  RowBox[{"b", " ", "uxyy"}], "+", 
  RowBox[{"bxy", " ", "uy"}], "+", 
  RowBox[{"bx", " ", "uyy"}]}]], "Output",
 CellChangeTimes->{{3.615064666647613*^9, 3.6150646911137342`*^9}, {
   3.615065335756137*^9, 3.6150654165344963`*^9}, {3.615065491388652*^9, 
   3.6150655207361593`*^9}, 3.615065633820779*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{"b", " ", "u3y"}], "+", 
  RowBox[{"axy", " ", "ux"}], "+", 
  RowBox[{"ay", " ", "uxx"}], "+", 
  RowBox[{"a", " ", "uxxy"}], "+", 
  RowBox[{"ax", " ", "uxy"}], "+", 
  RowBox[{"byy", " ", "uy"}], "+", 
  RowBox[{"2", " ", "by", " ", "uyy"}]}]], "Output",
 CellChangeTimes->{{3.615064666647613*^9, 3.6150646911137342`*^9}, {
   3.615065335756137*^9, 3.6150654165344963`*^9}, {3.615065491388652*^9, 
   3.6150655207361593`*^9}, 3.615065633822727*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{
  RowBox[{"F", "=", 
   RowBox[{
    RowBox[{"D", "[", 
     RowBox[{
      RowBox[{
       RowBox[{"a", "[", 
        RowBox[{"x", ",", "y"}], "]"}], 
       RowBox[{"D", "[", 
        RowBox[{
         RowBox[{"u", "[", 
          RowBox[{"x", ",", "y"}], "]"}], ",", "x"}], "]"}]}], ",", "x"}], 
     "]"}], "+", 
    RowBox[{"D", "[", 
     RowBox[{
      RowBox[{
       RowBox[{"b", "[", 
        RowBox[{"x", ",", "y"}], "]"}], 
       RowBox[{"D", "[", 
        RowBox[{
         RowBox[{"u", "[", 
          RowBox[{"x", ",", "y"}], "]"}], ",", "y"}], "]"}]}], ",", "y"}], 
     "]"}]}]}], ";"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"F", ",", "x"}], "]"}], "//", 
  "FullSimplify"}], "\[IndentingNewLine]", 
 RowBox[{
  RowBox[{"D", "[", 
   RowBox[{"F", ",", "y"}], "]"}], "//", "FullSimplify"}]}], "Input",
 CellChangeTimes->{{3.615074120526884*^9, 3.615074144135675*^9}}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{
    SuperscriptBox["b", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
        RowBox[{"x", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{
    SuperscriptBox["a", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"2", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"c", "[", "y", "]"}], " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{
    SuperscriptBox["b", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"c", "[", "y", "]"}], " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
         RowBox[{"y", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{
           SuperscriptBox["d", "\[Prime]",
            MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"d", "[", "x", "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
         RowBox[{"x", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"c", "[", "y", "]"}], " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"d", "[", "x", "]"}]}], "+", 
           RowBox[{
            RowBox[{"(", 
             RowBox[{
              RowBox[{"Sin", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], "+", 
              RowBox[{"x", " ", "y", " ", 
               RowBox[{"Cos", "[", 
                RowBox[{"x", " ", 
                 RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "+", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["c", "\[Prime]",
              MultilineFunction->None], "[", "y", "]"}]}], "-", 
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}], "+", 
              RowBox[{"y", " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
          ")"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{
    SuperscriptBox["b", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"d", "[", "x", "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
          RowBox[{"x", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["c", "\[Prime]",
             MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"2", " ", "x", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}], "+", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", 
             RowBox[{"Sin", "[", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
            RowBox[{"(", 
             RowBox[{
              SuperscriptBox[
               RowBox[{"d", "[", "x", "]"}], "2"], "+", 
              RowBox[{
               SuperscriptBox["x", "2"], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["c", "\[Prime]",
                  MultilineFunction->None], "[", "y", "]"}], "2"]}]}], 
             ")"}]}], "+", 
           RowBox[{"x", " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["c", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}]}], ")"}],
       "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{"b", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"c", "[", "y", "]"}], " ", 
              RowBox[{"Cos", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{"d", "[", "x", "]"}]}], "+", 
             RowBox[{
              RowBox[{"(", 
               RowBox[{
                RowBox[{"Sin", "[", 
                 RowBox[{"x", " ", 
                  RowBox[{"c", "[", "y", "]"}]}], "]"}], "+", 
                RowBox[{"x", " ", "y", " ", 
                 RowBox[{"Cos", "[", 
                  RowBox[{"x", " ", 
                   RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
                 RowBox[{
                  SuperscriptBox["c", "\[Prime]",
                   MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], " ", 
              
              RowBox[{
               SuperscriptBox["d", "\[Prime]",
                MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "+", 
          RowBox[{
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"Cos", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{
               SuperscriptBox["c", "\[Prime]",
                MultilineFunction->None], "[", "y", "]"}]}], "-", 
             RowBox[{
              RowBox[{"Sin", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{"(", 
               RowBox[{
                RowBox[{"x", " ", 
                 RowBox[{"c", "[", "y", "]"}], " ", 
                 RowBox[{
                  SuperscriptBox["c", "\[Prime]",
                   MultilineFunction->None], "[", "y", "]"}]}], "+", 
                RowBox[{"y", " ", 
                 RowBox[{"d", "[", "x", "]"}], " ", 
                 RowBox[{
                  SuperscriptBox["d", "\[Prime]",
                   MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
            ")"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"c", "[", "y", "]"}], " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
         RowBox[{"y", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{
           SuperscriptBox["d", "\[Prime]",
            MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"2", " ", "x", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"d", "[", "x", "]"}], " ", 
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}]}], "+", 
         RowBox[{
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"(", 
           RowBox[{
            RowBox[{
             RowBox[{"-", 
              RowBox[{"Sin", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
             RowBox[{"(", 
              RowBox[{
               SuperscriptBox[
                RowBox[{"d", "[", "x", "]"}], "2"], "+", 
               RowBox[{
                SuperscriptBox["x", "2"], " ", 
                SuperscriptBox[
                 RowBox[{
                  SuperscriptBox["c", "\[Prime]",
                   MultilineFunction->None], "[", "y", "]"}], "2"]}]}], 
              ")"}]}], "+", 
            RowBox[{"x", " ", 
             RowBox[{"Cos", "[", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
             RowBox[{
              SuperscriptBox["c", "\[Prime]\[Prime]",
               MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}]}], 
        ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"d", "[", "x", "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
          RowBox[{"x", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["c", "\[Prime]",
             MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"1", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", 
             RowBox[{"Cos", "[", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{"(", 
                RowBox[{
                 SuperscriptBox[
                  RowBox[{"d", "[", "x", "]"}], "2"], "+", 
                 RowBox[{
                  SuperscriptBox["x", "2"], " ", 
                  SuperscriptBox[
                   RowBox[{
                    SuperscriptBox["c", "\[Prime]",
                    MultilineFunction->None], "[", "y", "]"}], "2"]}]}], 
                ")"}]}], "+", 
              RowBox[{"2", " ", "x", " ", "y", " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}], "-", 
              RowBox[{
               SuperscriptBox["c", "\[Prime]\[Prime]",
                MultilineFunction->None], "[", "y", "]"}]}], ")"}]}], "-", 
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"2", " ", "x", " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["c", "\[Prime]",
                  MultilineFunction->None], "[", "y", "]"}], "2"]}], "+", 
              RowBox[{"2", " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}], "+", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}]}], 
          ")"}]}], "+", 
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", 
             RowBox[{"Sin", "[", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"2", " ", "x", " ", 
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}], "+", 
              RowBox[{"y", " ", 
               RowBox[{"(", 
                RowBox[{
                 SuperscriptBox[
                  RowBox[{"d", "[", "x", "]"}], "2"], "+", 
                 RowBox[{
                  SuperscriptBox["x", "2"], " ", 
                  SuperscriptBox[
                   RowBox[{
                    SuperscriptBox["c", "\[Prime]",
                    MultilineFunction->None], "[", "y", "]"}], "2"]}]}], 
                ")"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "+", 
           
           RowBox[{
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"2", " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}], " ", 
               RowBox[{"(", 
                RowBox[{
                 RowBox[{"d", "[", "x", "]"}], "+", 
                 RowBox[{"x", " ", 
                  RowBox[{
                   SuperscriptBox["d", "\[Prime]",
                    MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], 
              "+", 
              RowBox[{"x", " ", "y", " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}]}], 
          ")"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{"2", " ", 
   RowBox[{
    SuperscriptBox["a", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"c", "[", "y", "]"}], " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
          RowBox[{"y", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["d", "\[Prime]",
             MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"1", ",", "0"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"-", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           SuperscriptBox[
            RowBox[{"c", "[", "y", "]"}], "2"], "+", 
           RowBox[{
            SuperscriptBox["y", "2"], " ", 
            SuperscriptBox[
             RowBox[{
              SuperscriptBox["d", "\[Prime]",
               MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}]}], 
        "+", 
        RowBox[{"y", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{"2", " ", 
            RowBox[{"c", "[", "y", "]"}], " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}], "+", 
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], ")"}],
       "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{"a", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"3", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"-", 
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"(", 
            RowBox[{
             SuperscriptBox[
              RowBox[{"c", "[", "y", "]"}], "2"], "+", 
             RowBox[{
              SuperscriptBox["y", "2"], " ", 
              SuperscriptBox[
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}]}],
           "+", 
          RowBox[{"y", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"(", 
            RowBox[{
             RowBox[{"2", " ", 
              RowBox[{"c", "[", "y", "]"}], " ", 
              RowBox[{"Cos", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{
               SuperscriptBox["d", "\[Prime]",
                MultilineFunction->None], "[", "x", "]"}]}], "+", 
             RowBox[{
              RowBox[{"Sin", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{
               SuperscriptBox["d", "\[Prime]\[Prime]",
                MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
         ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"1", ",", "0"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{"3", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"c", "[", "y", "]"}], " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
          RowBox[{"y", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["d", "\[Prime]",
             MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"2", ",", "0"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"3", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"-", 
          RowBox[{"c", "[", "y", "]"}]}], " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"y", " ", 
              RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              SuperscriptBox[
               RowBox[{"c", "[", "y", "]"}], "2"], "+", 
              RowBox[{"3", " ", 
               SuperscriptBox["y", "2"], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["d", "\[Prime]",
                  MultilineFunction->None], "[", "x", "]"}], "2"]}]}], 
             ")"}]}], "-", 
           RowBox[{"3", " ", "y", " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"y", " ", 
              RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", "3"}], " ", "y", " ", 
            RowBox[{"Sin", "[", 
             RowBox[{"y", " ", 
              RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]",
              MultilineFunction->None], "[", "x", "]"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}], "+", 
           RowBox[{
            RowBox[{"Cos", "[", 
             RowBox[{"y", " ", 
              RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{
               RowBox[{"-", "3"}], " ", 
               SuperscriptBox[
                RowBox[{"c", "[", "y", "]"}], "2"], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}], "-", 
              RowBox[{
               SuperscriptBox["y", "2"], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["d", "\[Prime]",
                  MultilineFunction->None], "[", "x", "]"}], "3"]}], "+", 
              RowBox[{
               SuperscriptBox["d", 
                TagBox[
                 RowBox[{"(", "3", ")"}],
                 Derivative],
                MultilineFunction->None], "[", "x", "]"}]}], ")"}]}]}], 
          ")"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}]}]], "Output",
 CellChangeTimes->{3.615074126785408*^9, 3.61507420479605*^9}],

Cell[BoxData[
 RowBox[{
  RowBox[{
   RowBox[{
    SuperscriptBox["b", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "2"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
        RowBox[{"x", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{
    SuperscriptBox["a", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"c", "[", "y", "]"}], " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
        RowBox[{"y", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{
          SuperscriptBox["d", "\[Prime]",
           MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{
    SuperscriptBox["a", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"1", ",", "0"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"c", "[", "y", "]"}], " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
         RowBox[{"y", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{
           SuperscriptBox["d", "\[Prime]",
            MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"d", "[", "x", "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
         RowBox[{"x", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"1", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"c", "[", "y", "]"}], " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"d", "[", "x", "]"}]}], "+", 
           RowBox[{
            RowBox[{"(", 
             RowBox[{
              RowBox[{"Sin", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], "+", 
              RowBox[{"x", " ", "y", " ", 
               RowBox[{"Cos", "[", 
                RowBox[{"x", " ", 
                 RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "+", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["c", "\[Prime]",
              MultilineFunction->None], "[", "y", "]"}]}], "-", 
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}], "+", 
              RowBox[{"y", " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
          ")"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{"2", " ", 
   RowBox[{
    SuperscriptBox["b", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"d", "[", "x", "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
          RowBox[{"x", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["c", "\[Prime]",
             MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "2"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{"2", " ", "x", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{
          SuperscriptBox["c", "\[Prime]",
           MultilineFunction->None], "[", "y", "]"}]}], "+", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", 
             RowBox[{"Sin", "[", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
            RowBox[{"(", 
             RowBox[{
              SuperscriptBox[
               RowBox[{"d", "[", "x", "]"}], "2"], "+", 
              RowBox[{
               SuperscriptBox["x", "2"], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["c", "\[Prime]",
                  MultilineFunction->None], "[", "y", "]"}], "2"]}]}], 
             ")"}]}], "+", 
           RowBox[{"x", " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["c", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}]}], ")"}],
       "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{
    SuperscriptBox["a", 
     TagBox[
      RowBox[{"(", 
       RowBox[{"0", ",", "1"}], ")"}],
      Derivative],
     MultilineFunction->None], "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"c", "[", "y", "]"}], " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
          RowBox[{"y", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["d", "\[Prime]",
             MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"1", ",", "0"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"-", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           SuperscriptBox[
            RowBox[{"c", "[", "y", "]"}], "2"], "+", 
           RowBox[{
            SuperscriptBox["y", "2"], " ", 
            SuperscriptBox[
             RowBox[{
              SuperscriptBox["d", "\[Prime]",
               MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}]}], 
        "+", 
        RowBox[{"y", " ", 
         RowBox[{"Cos", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{"2", " ", 
            RowBox[{"c", "[", "y", "]"}], " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}], "+", 
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["d", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], ")"}],
       "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{"a", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"-", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"(", 
           RowBox[{
            SuperscriptBox[
             RowBox[{"c", "[", "y", "]"}], "2"], "+", 
            RowBox[{
             SuperscriptBox["y", "2"], " ", 
             SuperscriptBox[
              RowBox[{
               SuperscriptBox["d", "\[Prime]",
                MultilineFunction->None], "[", "x", "]"}], "2"]}]}], ")"}]}], 
         "+", 
         RowBox[{"y", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"(", 
           RowBox[{
            RowBox[{"2", " ", 
             RowBox[{"c", "[", "y", "]"}], " ", 
             RowBox[{"Cos", "[", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
             RowBox[{
              SuperscriptBox["d", "\[Prime]",
               MultilineFunction->None], "[", "x", "]"}]}], "+", 
            RowBox[{
             RowBox[{"Sin", "[", 
              RowBox[{"x", " ", 
               RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
             RowBox[{
              SuperscriptBox["d", "\[Prime]\[Prime]",
               MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
        ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"c", "[", "y", "]"}], " ", 
              RowBox[{"Cos", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{"d", "[", "x", "]"}]}], "+", 
             RowBox[{
              RowBox[{"(", 
               RowBox[{
                RowBox[{"Sin", "[", 
                 RowBox[{"x", " ", 
                  RowBox[{"c", "[", "y", "]"}]}], "]"}], "+", 
                RowBox[{"x", " ", "y", " ", 
                 RowBox[{"Cos", "[", 
                  RowBox[{"x", " ", 
                   RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
                 RowBox[{
                  SuperscriptBox["c", "\[Prime]",
                   MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], " ", 
              
              RowBox[{
               SuperscriptBox["d", "\[Prime]",
                MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}], "+", 
          RowBox[{
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"Cos", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{
               SuperscriptBox["c", "\[Prime]",
                MultilineFunction->None], "[", "y", "]"}]}], "-", 
             RowBox[{
              RowBox[{"Sin", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{"(", 
               RowBox[{
                RowBox[{"x", " ", 
                 RowBox[{"c", "[", "y", "]"}], " ", 
                 RowBox[{
                  SuperscriptBox["c", "\[Prime]",
                   MultilineFunction->None], "[", "y", "]"}]}], "+", 
                RowBox[{"y", " ", 
                 RowBox[{"d", "[", "x", "]"}], " ", 
                 RowBox[{
                  SuperscriptBox["d", "\[Prime]",
                   MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
            ")"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"1", ",", "0"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{"2", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"c", "[", "y", "]"}], " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}]}], "+", 
          RowBox[{"y", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["d", "\[Prime]",
             MultilineFunction->None], "[", "x", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"1", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{"d", "[", "x", "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
         RowBox[{"x", " ", 
          RowBox[{"Cos", "[", 
           RowBox[{"x", " ", 
            RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
          RowBox[{"Sin", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
          RowBox[{
           SuperscriptBox["c", "\[Prime]",
            MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "0"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"2", ",", "1"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", 
             RowBox[{"Cos", "[", 
              RowBox[{"y", " ", 
               RowBox[{"d", "[", "x", "]"}]}], "]"}]}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{
               SuperscriptBox[
                RowBox[{"c", "[", "y", "]"}], "2"], " ", 
               RowBox[{"d", "[", "x", "]"}]}], "+", 
              RowBox[{"2", " ", "x", " ", "y", " ", 
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}], "+", 
              RowBox[{
               SuperscriptBox["y", "2"], " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["d", "\[Prime]",
                  MultilineFunction->None], "[", "x", "]"}], "2"]}], "-", 
              RowBox[{
               SuperscriptBox["d", "\[Prime]\[Prime]",
                MultilineFunction->None], "[", "x", "]"}]}], ")"}]}], "-", 
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"y", " ", 
              RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"2", " ", 
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}], "+", 
              RowBox[{"2", " ", "y", " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["d", "\[Prime]",
                  MultilineFunction->None], "[", "x", "]"}], "2"]}], "+", 
              RowBox[{"y", " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
          ")"}]}], "+", 
        RowBox[{
         RowBox[{"Cos", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", 
             RowBox[{"Sin", "[", 
              RowBox[{"y", " ", 
               RowBox[{"d", "[", "x", "]"}]}], "]"}]}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"x", " ", 
               SuperscriptBox[
                RowBox[{"c", "[", "y", "]"}], "2"], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}], "+", 
              RowBox[{"2", " ", "y", " ", 
               RowBox[{"c", "[", "y", "]"}], " ", 
               RowBox[{"d", "[", "x", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}], "+", 
              RowBox[{"x", " ", 
               SuperscriptBox["y", "2"], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["d", "\[Prime]",
                  MultilineFunction->None], "[", "x", "]"}], "2"]}]}], 
             ")"}]}], "+", 
           RowBox[{
            RowBox[{"Cos", "[", 
             RowBox[{"y", " ", 
              RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{"2", " ", 
               RowBox[{"(", 
                RowBox[{
                 RowBox[{"c", "[", "y", "]"}], "+", 
                 RowBox[{"y", " ", 
                  RowBox[{
                   SuperscriptBox["c", "\[Prime]",
                    MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}], "+", 
              RowBox[{"x", " ", "y", " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}], " ", 
               RowBox[{
                SuperscriptBox["d", "\[Prime]\[Prime]",
                 MultilineFunction->None], "[", "x", "]"}]}]}], ")"}]}]}], 
          ")"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}], "+", 
  RowBox[{
   RowBox[{"b", "[", 
    RowBox[{"x", ",", "y"}], "]"}], " ", 
   RowBox[{"(", 
    RowBox[{
     RowBox[{"3", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{"2", " ", "x", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"d", "[", "x", "]"}], " ", 
           RowBox[{
            SuperscriptBox["c", "\[Prime]",
             MultilineFunction->None], "[", "y", "]"}]}], "+", 
          RowBox[{
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"(", 
            RowBox[{
             RowBox[{
              RowBox[{"-", 
               RowBox[{"Sin", "[", 
                RowBox[{"x", " ", 
                 RowBox[{"c", "[", "y", "]"}]}], "]"}]}], " ", 
              RowBox[{"(", 
               RowBox[{
                SuperscriptBox[
                 RowBox[{"d", "[", "x", "]"}], "2"], "+", 
                RowBox[{
                 SuperscriptBox["x", "2"], " ", 
                 SuperscriptBox[
                  RowBox[{
                   SuperscriptBox["c", "\[Prime]",
                    MultilineFunction->None], "[", "y", "]"}], "2"]}]}], 
               ")"}]}], "+", 
             RowBox[{"x", " ", 
              RowBox[{"Cos", "[", 
               RowBox[{"x", " ", 
                RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
              RowBox[{
               SuperscriptBox["c", "\[Prime]\[Prime]",
                MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}]}], 
         ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "1"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{"3", " ", 
      RowBox[{
       SuperscriptBox[
        RowBox[{"(", 
         RowBox[{
          RowBox[{
           RowBox[{"Cos", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{"d", "[", "x", "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}]}], "+", 
          RowBox[{"x", " ", 
           RowBox[{"Cos", "[", 
            RowBox[{"x", " ", 
             RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
           RowBox[{"Sin", "[", 
            RowBox[{"y", " ", 
             RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
           RowBox[{
            SuperscriptBox["c", "\[Prime]",
             MultilineFunction->None], "[", "y", "]"}]}]}], ")"}], 
        TagBox[
         RowBox[{"(", 
          RowBox[{"0", ",", "2"}], ")"}],
         Derivative],
        MultilineFunction->None], "[", 
       RowBox[{"x", ",", "y"}], "]"}]}], "+", 
     RowBox[{
      SuperscriptBox[
       RowBox[{"(", 
        RowBox[{
         RowBox[{"Sin", "[", 
          RowBox[{"x", " ", 
           RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}]}], ")"}], 
       TagBox[
        RowBox[{"(", 
         RowBox[{"0", ",", "3"}], ")"}],
        Derivative],
       MultilineFunction->None], "[", 
      RowBox[{"x", ",", "y"}], "]"}], "+", 
     RowBox[{
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"-", 
          RowBox[{"Cos", "[", 
           RowBox[{"y", " ", 
            RowBox[{"d", "[", "x", "]"}]}], "]"}]}], " ", 
         RowBox[{"d", "[", "x", "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              SuperscriptBox[
               RowBox[{"d", "[", "x", "]"}], "2"], "+", 
              RowBox[{"3", " ", 
               SuperscriptBox["x", "2"], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["c", "\[Prime]",
                  MultilineFunction->None], "[", "y", "]"}], "2"]}]}], 
             ")"}]}], "-", 
           RowBox[{"3", " ", "x", " ", 
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["c", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "y", "]"}]}]}], ")"}]}], "+", 
        RowBox[{"x", " ", 
         RowBox[{"Sin", "[", 
          RowBox[{"y", " ", 
           RowBox[{"d", "[", "x", "]"}]}], "]"}], " ", 
         RowBox[{"(", 
          RowBox[{
           RowBox[{
            RowBox[{"-", "3"}], " ", "x", " ", 
            RowBox[{"Sin", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{
             SuperscriptBox["c", "\[Prime]",
              MultilineFunction->None], "[", "y", "]"}], " ", 
            RowBox[{
             SuperscriptBox["c", "\[Prime]\[Prime]",
              MultilineFunction->None], "[", "y", "]"}]}], "+", 
           RowBox[{
            RowBox[{"Cos", "[", 
             RowBox[{"x", " ", 
              RowBox[{"c", "[", "y", "]"}]}], "]"}], " ", 
            RowBox[{"(", 
             RowBox[{
              RowBox[{
               RowBox[{"-", "3"}], " ", 
               SuperscriptBox[
                RowBox[{"d", "[", "x", "]"}], "2"], " ", 
               RowBox[{
                SuperscriptBox["c", "\[Prime]",
                 MultilineFunction->None], "[", "y", "]"}]}], "-", 
              RowBox[{
               SuperscriptBox["x", "2"], " ", 
               SuperscriptBox[
                RowBox[{
                 SuperscriptBox["c", "\[Prime]",
                  MultilineFunction->None], "[", "y", "]"}], "3"]}], "+", 
              RowBox[{
               SuperscriptBox["c", 
                TagBox[
                 RowBox[{"(", "3", ")"}],
                 Derivative],
                MultilineFunction->None], "[", "y", "]"}]}], ")"}]}]}], 
          ")"}]}]}], ")"}], "[", 
      RowBox[{"x", ",", "y"}], "]"}]}], ")"}]}]}]], "Output",
 CellChangeTimes->{3.615074126785408*^9, 3.61507423170282*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot3D", "[", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{
     RowBox[{"Sin", "[", "x", "]"}], 
     RowBox[{"Sin", "[", 
      RowBox[{"3", "y"}], "]"}]}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", 
     RowBox[{"-", "1.1"}], ",", "1.1"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", 
     RowBox[{"-", "1.1"}], ",", "1.1"}], "}"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.615148608579664*^9, 3.615148654685828*^9}, {
  3.6152072418919*^9, 3.615207311803288*^9}, {3.615207957094335*^9, 
  3.615207979871079*^9}, {3.6152080128459167`*^9, 3.615208055883617*^9}, {
  3.615748258702489*^9, 3.615748388639921*^9}}],

Cell[BoxData[
 Graphics3DBox[GraphicsComplex3DBox[CompressedData["
1:eJx1fXd8kDX3PbL3kj0UFVEQQRFkVQOoIKjIkg3KeAHZSxBBtiyZgsjee+9Z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   "], {{
     {EdgeForm[None], GraphicsGroup3DBox[{Polygon3DBox[CompressedData["
1:eJxFnHUcFkX39u/tQAQUVMLAbkDFBJRGsWlEEQXsRlQUDCxEBEXFLmwUuwsD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         "]], 
        Polygon3DBox[CompressedData["
1:eJwtnHfgTuUbxs953zPfllm0EJXQNBpKRoSM0CQKRZOGUCiyRdp7CYVK2kOp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         "]], Polygon3DBox[CompressedData["
1:eJwt1wncjlUax/FH7/u8z/O+kSYaqamGss2kRWnBVFNSEsmeChmRnbJEyVa2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         "]], 
        Polygon3DBox[{{2386, 1038, 899, 898, 1218, 1959}, {1928, 1176, 984, 
         985, 1177, 1929}, {1909, 1147, 915, 916, 1148, 1910}, {1735, 1734, 
         2422, 1152, 1153, 2423}, {2405, 1095, 968, 967, 1297, 2050}, {1871, 
         1069, 1157, 2427, 1741, 1742}}]}]}, {}, {}, {}, {}}, {
     {GrayLevel[0], Line3DBox[CompressedData["
1:eJwl0ktIVFEYB/DPx2QvnZahYg9woxS0nxatBBWD3CmRiGQZKiGBOtCqSBBX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       "]]}, {
      Line3DBox[{1659, 1937, 1016, 1658, 2485, 1835, 1660, 2486, 1836, 1661, 
       2487, 1837, 1662, 2418, 2488, 2115, 1838, 1938, 2419, 2489, 1940, 1839,
        1939, 2596, 2218, 2219, 1942, 2209, 2382, 2662, 1941, 2220, 2221, 
       1944, 2210, 2597, 1840, 1943, 1900, 2490, 1841, 1945, 1901, 2491, 1842,
        1663, 2492, 1843, 1664, 2493, 1844, 1665, 2494, 1845, 1666, 2598, 
       1946, 1846, 1947}], 
      Line3DBox[{1668, 1948, 2116, 2383, 2599, 1667, 1950, 2117, 1028, 1669, 
       1952, 2118, 2650, 1847, 1670, 2438, 2495, 2119, 1848, 1671, 2437, 2496,
        2120, 1849, 1954, 2602, 1902, 2121, 1850, 1956, 2604, 1903, 2122, 
       2384, 2586, 1958, 1904, 2385, 2587, 1960, 1905, 2497, 1851, 1672, 1906,
        2498, 1852, 1673, 2499, 1853, 1674, 2482, 2500, 2346, 1854, 1675, 
       2501, 1855, 1676, 2502, 1856, 1677}], 
      Line3DBox[{1712, 2006, 2156, 2007, 2618, 1711, 2009, 2157, 2547, 2445, 
       1713, 2342, 2343, 2548, 2369, 2368, 1714, 2376, 2377, 2692, 2375, 2367,
        1715, 2420, 2549, 1907, 1716, 1145, 1908, 1717, 2589, 1909, 1910, 
       2588, 1718, 1911, 2012, 1912, 2590, 1719, 1913, 2013, 2550, 2421, 1720,
        2014, 2158, 2551, 2446, 1721, 2447, 2652, 2159, 2015, 1722, 2448, 
       2653, 2160, 2016, 1723, 2620, 2017, 2161, 2018, 1724, 2621, 2019, 2162,
        2020, 1725}], 
      Line3DBox[{1729, 2508, 1863, 1727, 2509, 1864, 1731, 2510, 1865, 1733, 
       2511, 1866, 1735, 2423, 2512, 1867, 2025, 2425, 2513, 2027, 2211, 1868,
        2026, 2463, 2664, 2225, 2029, 2212, 1066, 2028, 2229, 2230, 2031, 
       2213, 2623, 1869, 2030, 2231, 2232, 2033, 2624, 1870, 2032, 1918, 2514,
        1871, 1742, 2515, 1872, 1744, 2516, 1873, 1746, 2517, 1874, 1748, 
       2519, 1876, 1750}], 
      Line3DBox[{1749, 1875, 2518, 1747, 2561, 2398, 1745, 2560, 2397, 1743, 
       2559, 2396, 1741, 2427, 2558, 2024, 1917, 1740, 2426, 2557, 2023, 1916,
        1739, 2464, 2665, 2228, 2022, 2227, 2226, 1738, 2622, 2223, 2224, 
       2021, 2222, 1426, 1737, 1915, 2277, 2672, 2424, 1736, 1914, 2556, 2422,
        1734, 2555, 2395, 1732, 2554, 2394, 1730, 2553, 2393, 1726, 2552, 
       2392, 1728}], 
      Line3DBox[{1752, 2399, 2562, 1751, 2520, 1877, 1753, 2521, 1878, 1754, 
       2522, 1879, 1755, 2428, 2523, 2163, 1880, 2034, 2429, 2524, 2036, 1881,
        2035, 2625, 2233, 2234, 2038, 2214, 2400, 2663, 2037, 2235, 2236, 
       2040, 2215, 1079, 2039, 1919, 2281, 2673, 1882, 2041, 1920, 2525, 1883,
        1756, 2526, 1884, 1757, 2527, 1885, 1758, 2528, 1886, 1759, 2529, 
       1887, 1760}], 
      Line3DBox[{1762, 2042, 2164, 2401, 2626, 1761, 2044, 2165, 2402, 2628, 
       1763, 2046, 2166, 2654, 1888, 1764, 2450, 2530, 2167, 1889, 1765, 2449,
        2531, 2168, 1890, 1766, 2591, 1921, 2169, 1891, 1767, 2593, 1922, 
       2170, 2403, 2592, 1768, 1923, 2404, 2594, 2282, 1924, 1091, 1769, 1925,
        2532, 1892, 1770, 2533, 1893, 1771, 2483, 2534, 2349, 1894, 1772, 
       2634, 2051, 2171, 1895, 1773, 2635, 2053, 2172, 1896, 1774}], 
      Line3DBox[{1807, 2411, 2569, 1806, 2373, 2374, 2484, 2694, 2381, 1808, 
       2344, 2345, 2570, 2372, 2371, 1809, 2379, 2380, 2693, 2378, 2370, 1810,
        2430, 2571, 1926, 1811, 2431, 2572, 1927, 1812, 2595, 1928, 1929, 
       2646, 1813, 1930, 2100, 1931, 2648, 1814, 1932, 2101, 2573, 2432, 1815,
        2102, 2202, 2574, 2459, 1816, 2460, 2658, 2203, 2103, 1817, 2461, 
       2659, 2204, 2104, 1818, 1341, 2205, 2105, 1819, 2645, 2106, 2206, 2107,
        1820}], 
      Line3DBox[{1834, 2114, 1356, 1833, 2585, 2417, 1832, 2584, 2416, 1831, 
       2583, 2415, 1830, 2436, 2582, 2111, 1936, 1829, 2435, 2581, 2110, 1935,
        1828, 2466, 2666, 2242, 2109, 2241, 2240, 1827, 2649, 2238, 2239, 
       2108, 2237, 2647, 2465, 1826, 1934, 2580, 2434, 1825, 1933, 2579, 2433,
        1824, 2578, 2414, 1823, 2577, 2413, 1822, 2576, 2412, 1821, 2462, 
       2575, 2112, 2113}], Line3DBox[CompressedData["
1:eJwVzd0qA3AYx/GHxDh1Be7AzFyF1losSWpOyc4duQmMeY0dbJi3vERkmRVK
afeBlQvYx8Gv7/N8f/+n/8hCMbfcExFZaQ5E/CYiOlI1T2INF4ciDgcj1voj
XrhjLoMnuKRrmtd1vd6ccll7HVd0w9yGrtUXkePP+JJ9VHdunuIucJNLcpfm
PHeFW9yb+2n5lrI9jz+ybX735kMm3O3Yr80zbm9wldvlxvDWPsvf4d7/3+5T
/L19jn/AT9zXHenGdY/cPPeEr3igq+jSumeuwDXwD7+kLV26NjIw
       "]], 
      Line3DBox[CompressedData["
1:eJwVzDsvA2AUxvEjocWMzuZOJhqdfQCJ2Ks3JEwsJqPyKVyrLh+ionW/lCai
PgQV5v46PPmf83/O+07m1ufXBiJiQT6SEX/DEf9SN+fwCluYH43YT0Q0zNfc
EjZwix8biTjQdbkml8dvbkfG5VA3hBXZcF/Q37ibsB/pvgYjitwtd2y/4+fM
J+Z786L8SNX+yXdk1j+n9gdzydtHnOZq3JO5zHW92ZUzbgqzsifb7jL47C6F
5/oEzvAv3LK3r/iLF7qaLqNrcSvcGzbxUrfJJ/Xv3CrXxnR/78/SA7P2Nj0=

       "]], Line3DBox[CompressedData["
1:eJwV0L0ug2EYxvG7NNV27CA+SnS3cQaCMjaOoEmJDowsIiKNCBGJmGusWDgL
R0A4AO3mowMlwu8Z/rmu+7qe+3nfPJX6dm0rExFrmMxHPOMHTzhHDsVCRKMY
ccVfo4MzZLErv9G/8D10cYpR7OgKum++Qmdwks7RS8xjDqvZiGN5Cf2ce+1t
yD/4YX6df+erfIMfcm6Ff5M1RyKOzBksy15lm7KWObAnK9uZxhQO0z/SC+Tx
ZZ6gS87d0QPzn/0B/cS4bFF3S/fNv7p72k7vIFvQPaTvpHfTzcoe+TH6Dz3w
Ld8=
       "]], Line3DBox[CompressedData["
1:eJwVyzlKg1EUBtBrkdExqDhF1BTaC1oE3IEzZAOptDDZgIQQRUQQEVyDNm7E
YQEB3YB94phfPSkO997ve2+pWt+vDUREhcVsRI+EDA2yHOUjbnMRnXTEgztH
kzw1Xdvs6h7NQVoMcayb8+9dt2re0JKd6oZZcH/oNmUj7jNG+ZRtycbs5xT4
kr15f0BK9+0+tKftP/Zlb1bYc/fc4/YLJjiRJbI17zcopSLK5qSuZP7q1s1t
76Zkl0zzxJ/uXrejm3FfMcszkYm40+3qiu5r5vu57MV85R8ATSlL
       "]], 
      Line3DBox[CompressedData["
1:eJwVz0tOAmEUROGLiN28tqBBIEEBURlIQsIaDDhXGWqiiTMmsAdQHu7BJcEC
dA/K5+Ckbp36e9CV8evwJRMRt7hKIzL5iGM5xwmq+luBTyKK7gp3IU/llK+5
D2wl2UOV78iZbSnryNpX8p5b2Gs45NbcA/eu15HjvrlneYQf9xMSbxL92psu
7vRUb7g/cIYhl+fO3Uuk+sa3Be5TPuorvokid8MN0M1F9GWL/0XJ9qWPvG/r
6///xR/Ktglftnf0DS6xxQ57mFsc1g==
       "]], Line3DBox[CompressedData["
1:eJwNy7tKwgEUx/ETSZZDF32CtiKqZ+g2hYZaREgUPUD/od4hp+5riIhIiy0t
QdBYS9Qb2MVNrVfwM3z53c6ZPUpKxyMRUcDBeMQnPnCIl3REaiIiyUT8yF38
Yh/PtlP9vb0jf+MLFTzZTmyjtn95Q96jb3IVt2MR67qKm139I3+jG9i2cc33
aRlX/JK7Et9yt8xf6tb4Hb9Nuqi70K3yZV2DLujOdSt8Uffq/wwzyCJn29LX
7X90gGn9vL8Hmpdrtj7toa2bs03STfnO9k6n5CG7/Cto
       "]]}, {
      Line3DBox[{864, 1017, 2485, 865, 1201, 1028, 888, 1202, 1502, 2601, 
       1550, 1551, 1552, 1450, 1220, 2668, 1399, 1473, 1474, 1562, 1561, 1240,
        2683, 1479, 1480, 1481, 911, 2547, 1254, 1056, 921, 2553, 1063, 2509, 
       934, 1075, 2520, 947, 1283, 2628, 1087, 959, 1510, 1284, 1509, 2629, 
       1570, 1571, 1572, 1476, 1302, 2670, 1407, 1419, 1420, 1585, 1584, 1602,
        1320, 2686, 1518, 1650, 1651, 980, 2694, 1657, 1649, 1656, 1113, 990, 
       2576, 1120, 1004}], 
      Line3DBox[{866, 1018, 2486, 867, 1203, 1029, 2650, 889, 1204, 1553, 
       1555, 1556, 1560, 1559, 1221, 2682, 1557, 1563, 1564, 1566, 1565, 2544,
        1241, 1482, 1626, 1627, 912, 1643, 2548, 1590, 1641, 1057, 922, 2554, 
       1064, 2510, 935, 1076, 2521, 948, 1285, 1088, 2654, 960, 1513, 1286, 
       1511, 2630, 1573, 1574, 1578, 1577, 1303, 2684, 1575, 1586, 1587, 1589,
        1588, 1603, 2687, 1321, 1487, 1628, 1629, 981, 1648, 2570, 1591, 1646,
        1114, 991, 2577, 1121, 1005}], 
      Line3DBox[{868, 1019, 2487, 869, 1205, 1206, 2495, 1361, 1207, 1554, 
       1208, 2503, 1365, 1222, 1558, 1223, 1605, 1370, 1528, 2677, 1242, 1483,
        1243, 1652, 1653, 2692, 1639, 1642, 1640, 923, 2555, 1065, 2511, 936, 
       1077, 2522, 949, 1287, 1288, 2530, 1379, 1289, 1512, 1290, 2535, 1536, 
       1385, 1614, 2690, 1304, 1576, 1305, 1390, 2655, 1322, 1488, 1323, 1654,
        1655, 2693, 1644, 1647, 1645, 992, 2578, 1122, 1006}], 
      Line3DBox[{870, 1130, 1131, 2488, 1360, 1189, 1190, 2496, 1362, 1210, 
       2603, 1211, 1366, 1224, 2608, 1567, 1225, 1371, 1244, 1568, 1245, 913, 
       2549, 1143, 1144, 924, 2556, 1152, 1153, 2512, 937, 1158, 1159, 2523, 
       1378, 1274, 1275, 2531, 1380, 1291, 1579, 2685, 1292, 1386, 1306, 2636,
        1580, 1307, 1391, 2656, 1324, 1325, 982, 2571, 1172, 1173, 993, 2579, 
       1181, 1182, 1007}], 
      Line3DBox[{871, 1132, 1188, 1133, 2489, 1192, 1136, 1209, 2602, 1137, 
       1363, 1213, 2605, 1214, 1367, 1226, 2609, 1227, 904, 1049, 2506, 914, 
       1145, 1146, 1485, 2672, 1154, 1266, 1155, 2513, 1268, 1160, 1273, 1161,
        2524, 1277, 1164, 2591, 1165, 1381, 1293, 2631, 1294, 1387, 1308, 
       2637, 1309, 973, 1106, 2538, 983, 2572, 1174, 1175, 994, 2580, 1183, 
       1351, 1184, 1008}], 
      Line3DBox[{872, 1491, 1492, 1191, 1423, 2596, 1422, 1194, 1138, 1212, 
       2604, 1139, 1364, 1216, 2607, 1218, 898, 1043, 2505, 905, 1050, 2507, 
       915, 1147, 2589, 1484, 1149, 1265, 1426, 1427, 1267, 1431, 1430, 2664, 
       1270, 1434, 1435, 1276, 1439, 2625, 1438, 1279, 1166, 2593, 1168, 1382,
        1295, 2633, 1297, 967, 1100, 2537, 974, 1107, 2539, 984, 1176, 2595, 
       1345, 1178, 1347, 2647, 1442, 1443, 1352, 1500, 1499, 1489}], 
      Line3DBox[{875, 1134, 1196, 1022, 2490, 876, 1141, 1032, 2497, 892, 
       2541, 1040, 901, 1246, 2614, 1046, 908, 1247, 2615, 1053, 918, 2550, 
       1151, 1060, 927, 2557, 1156, 1272, 1068, 2624, 940, 1162, 1281, 1080, 
       2673, 952, 1170, 1091, 963, 2564, 1097, 970, 1326, 2641, 1103, 977, 
       1327, 2642, 1110, 987, 2573, 1180, 1349, 1117, 997, 2581, 1185, 1355, 
       1125, 1011}], 
      Line3DBox[{877, 1135, 1023, 2491, 878, 1142, 1033, 2498, 893, 1228, 
       1041, 2651, 902, 1229, 2688, 1606, 1047, 909, 2546, 1248, 1609, 1054, 
       919, 2551, 1256, 1061, 928, 2558, 1157, 1069, 2514, 941, 1163, 1081, 
       2525, 953, 1171, 1092, 2532, 964, 1310, 1615, 1098, 971, 1311, 2691, 
       1618, 1104, 978, 2568, 1328, 1111, 988, 2574, 1336, 1118, 998, 2582, 
       1186, 1126, 1012}], 
      Line3DBox[{879, 1024, 2492, 880, 1034, 2499, 894, 1230, 1231, 2504, 
       1368, 1232, 2610, 1607, 1233, 1608, 1372, 1610, 1630, 2689, 1249, 1634,
        1250, 1633, 1374, 2652, 1257, 1258, 929, 2559, 1070, 2515, 942, 1082, 
       2526, 954, 1093, 2533, 965, 1312, 1616, 1313, 2536, 1617, 1388, 1619, 
       1631, 1314, 1636, 1315, 1635, 1392, 2657, 1329, 1330, 1394, 2658, 1337,
        1338, 999, 2583, 1127, 1013}], 
      Line3DBox[{881, 1025, 2493, 882, 1594, 1595, 2500, 1596, 1597, 1234, 
       1503, 2675, 1235, 1521, 1369, 1604, 1236, 2611, 1569, 1237, 1611, 1373,
        1529, 1251, 2616, 1505, 1252, 1506, 1375, 2653, 1259, 1260, 930, 2560,
        1071, 2516, 943, 1083, 2527, 955, 1598, 1599, 2534, 1600, 1601, 1316, 
       1516, 2679, 1317, 1537, 1389, 1620, 1318, 2638, 1581, 1319, 1622, 1393,
        1623, 1632, 1331, 1638, 1332, 1637, 1395, 2659, 1339, 1340, 1000, 
       2584, 1128, 1014}], 
      Line3DBox[{883, 1026, 2494, 884, 1035, 2501, 895, 1238, 1477, 2676, 
       1523, 1522, 1524, 1451, 1452, 2612, 1400, 1531, 1530, 1612, 1532, 1533,
        2617, 1504, 1508, 1507, 1376, 1261, 2620, 1262, 931, 2561, 1072, 2517,
        944, 1084, 2528, 956, 1298, 2634, 1299, 1383, 1514, 1515, 1486, 2680, 
       1539, 1538, 1621, 1540, 1541, 2639, 1408, 1466, 1465, 1624, 1545, 1546,
        2643, 1519, 1333, 1396, 1341, 1342, 1001, 2585, 1129, 1015}], 
      Line3DBox[{885, 1197, 2598, 1198, 886, 1036, 2502, 896, 1239, 1478, 
       1526, 2671, 1525, 1527, 1453, 1454, 2613, 1401, 1456, 1455, 1613, 1534,
        2678, 1535, 1403, 1458, 1457, 1377, 1263, 2621, 1264, 932, 1073, 2518,
        2519, 945, 1085, 2529, 957, 1300, 2635, 1301, 1384, 1461, 1462, 1405, 
       1543, 2661, 1542, 1544, 1467, 1468, 2640, 1409, 1470, 1469, 1625, 1547,
        2681, 1548, 1520, 1334, 1397, 1343, 2645, 1344, 1002, 1356, 1357, 
       1358}], Line3DBox[{1003, 1119, 1350, 2575, 989, 1112, 2569, 979, 1105, 
       1517, 1583, 2674, 1582, 972, 1099, 1418, 1406, 2669, 1464, 1463, 966, 
       1094, 1475, 2627, 1404, 1460, 1459, 958, 1086, 2626, 1282, 946, 1074, 
       2562, 933, 2508, 1062, 2552, 920, 1055, 2618, 1253, 910, 1048, 1413, 
       1402, 1472, 2660, 1471, 903, 1042, 1412, 1398, 2667, 1449, 1448, 897, 
       1037, 1549, 2600, 1501, 1200, 887, 1027, 2599, 1199, 863, 1016, 1187, 
       1359}], Line3DBox[{1009, 1123, 1592, 1353, 1445, 2649, 1444, 995, 1115,
        1421, 1346, 2646, 1177, 985, 1108, 2567, 975, 1101, 2565, 968, 1095, 
       2632, 1296, 961, 1089, 2592, 1167, 950, 1078, 2663, 1416, 1278, 1437, 
       1436, 938, 1066, 1414, 1269, 1429, 2622, 1428, 925, 1058, 2588, 1148, 
       916, 1051, 2545, 906, 1044, 2542, 899, 1038, 2606, 1217, 890, 1030, 
       2586, 1215, 1425, 1424, 873, 1020, 2662, 1410, 1193, 1494, 1493, 
       1490}], Line3DBox[{1010, 1124, 1593, 1354, 1447, 1446, 2666, 996, 1116,
        1348, 2648, 1179, 986, 1109, 2644, 1335, 976, 1102, 2566, 969, 1096, 
       2563, 962, 1090, 2594, 1498, 1169, 951, 1079, 1417, 1280, 1441, 1440, 
       939, 2623, 1067, 1415, 1271, 1433, 1432, 2665, 926, 1059, 2590, 1150, 
       917, 1052, 2619, 1255, 907, 1045, 2543, 900, 1039, 2540, 891, 1031, 
       2587, 1219, 1140, 874, 2597, 1021, 1411, 1195, 1497, 1496, 
       1495}]}, {}, {}}},
   VertexNormals->CompressedData["
1:eJx0fXk81d/zP+1JKu279pX2TTQV0aKS9rTRol2KaC8RJaFCi4q0aFXSriYh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    "]],
  Axes->True,
  BoxRatios->{1, 1, 0.4},
  ImageSize->{947.0901869583713, 439.},
  Method->{"RotationControl" -> "Globe"},
  PlotRange->{{-1.1, 1.1}, {-1.1, 1.1}, {-0.8905415918653293, 
   0.8905415918653293}},
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02], 
    Scaled[0.02]},
  ViewPoint->{2.3452940546666383`, -1.9818065413330193`, 1.4219840469833178`},
  
  ViewVertical->{0., 0., 1.}]], "Output",
 CellChangeTimes->{{3.615148641601375*^9, 3.615148655339539*^9}, {
  3.615207285328375*^9, 3.615207312615196*^9}, {3.615207966905429*^9, 
  3.615207980825696*^9}, {3.615208021306891*^9, 3.6152080570322323`*^9}, {
  3.615748276826194*^9, 3.615748389154047*^9}}]
}, Open  ]],

Cell[BoxData[
 RowBox[{"x", "=."}]], "Input",
 CellChangeTimes->{{3.615325115667821*^9, 3.615325150958509*^9}, {
  3.615325193666006*^9, 3.615325193743863*^9}}],

Cell[CellGroupData[{

Cell[BoxData[{
 RowBox[{"M", "=", 
  RowBox[{"{", 
   RowBox[{
    RowBox[{"{", 
     RowBox[{"a", ",", "b"}], "}"}], ",", 
    RowBox[{"{", 
     RowBox[{"c", ",", "d"}], "}"}]}], "}"}]}], "\[IndentingNewLine]", 
 RowBox[{"B", "=", 
  RowBox[{"{", 
   RowBox[{"1", ",", "1"}], "}"}]}], "\[IndentingNewLine]", 
 RowBox[{"X", "=", 
  RowBox[{"LinearSolve", "[", 
   RowBox[{"M", ",", "B"}], "]"}]}], "\[IndentingNewLine]", 
 RowBox[{
  SqrtBox[
   RowBox[{
    FractionBox["1", 
     SuperscriptBox[
      RowBox[{"X", "[", 
       RowBox[{"[", "1", "]"}], "]"}], "2"]], "-", 
    FractionBox["1", 
     SuperscriptBox[
      RowBox[{"X", "[", 
       RowBox[{"[", "2", "]"}], "]"}], "2"]]}]], "//", 
  "Expand"}], "\[IndentingNewLine]", 
 RowBox[{"%", "/.", 
  RowBox[{"{", 
   RowBox[{
    RowBox[{"a", "\[Rule]", "0"}], ",", 
    RowBox[{"b", "\[Rule]", "0"}]}], "}"}]}], "\[IndentingNewLine]"}], "Input",\

 CellChangeTimes->{{3.615324972540607*^9, 3.615325108437948*^9}, {
  3.615325143685009*^9, 3.615325184348936*^9}, {3.615325251669273*^9, 
  3.615325281442421*^9}, {3.615325333605*^9, 3.615325356918264*^9}, {
  3.615325388819202*^9, 3.6153253919145737`*^9}, {3.615325454286963*^9, 
  3.615325468367283*^9}, {3.615325560614872*^9, 3.615325564701827*^9}, {
  3.615325614608732*^9, 3.615325643549505*^9}, {3.615325725772956*^9, 
  3.615325746672101*^9}, {3.6153257806340733`*^9, 3.615325785181685*^9}, {
  3.61532583592778*^9, 3.615325867523696*^9}}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   RowBox[{"{", 
    RowBox[{"a", ",", "b"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"c", ",", "d"}], "}"}]}], "}"}]], "Output",
 CellChangeTimes->{{3.61532503575928*^9, 3.6153250492170773`*^9}, {
   3.615325109195457*^9, 3.615325119328861*^9}, {3.6153251543721523`*^9, 
   3.615325196955284*^9}, {3.615325254430235*^9, 3.615325282308033*^9}, 
   3.6153253579311953`*^9, 3.615325396977257*^9, {3.615325459977042*^9, 
   3.615325469509162*^9}, 3.6153255667839518`*^9, {3.6153256235418167`*^9, 
   3.615325644074677*^9}, {3.615325730297449*^9, 3.615325748330233*^9}, 
   3.6153258694392014`*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{"1", ",", "1"}], "}"}]], "Output",
 CellChangeTimes->{{3.61532503575928*^9, 3.6153250492170773`*^9}, {
   3.615325109195457*^9, 3.615325119328861*^9}, {3.6153251543721523`*^9, 
   3.615325196955284*^9}, {3.615325254430235*^9, 3.615325282308033*^9}, 
   3.6153253579311953`*^9, 3.615325396977257*^9, {3.615325459977042*^9, 
   3.615325469509162*^9}, 3.6153255667839518`*^9, {3.6153256235418167`*^9, 
   3.615325644074677*^9}, {3.615325730297449*^9, 3.615325748330233*^9}, 
   3.6153258694428177`*^9}],

Cell[BoxData[
 RowBox[{"{", 
  RowBox[{
   FractionBox[
    RowBox[{
     RowBox[{"-", "b"}], "+", "d"}], 
    RowBox[{
     RowBox[{
      RowBox[{"-", "b"}], " ", "c"}], "+", 
     RowBox[{"a", " ", "d"}]}]], ",", 
   FractionBox[
    RowBox[{"a", "-", "c"}], 
    RowBox[{
     RowBox[{
      RowBox[{"-", "b"}], " ", "c"}], "+", 
     RowBox[{"a", " ", "d"}]}]]}], "}"}]], "Output",
 CellChangeTimes->{{3.61532503575928*^9, 3.6153250492170773`*^9}, {
   3.615325109195457*^9, 3.615325119328861*^9}, {3.6153251543721523`*^9, 
   3.615325196955284*^9}, {3.615325254430235*^9, 3.615325282308033*^9}, 
   3.6153253579311953`*^9, 3.615325396977257*^9, {3.615325459977042*^9, 
   3.615325469509162*^9}, 3.6153255667839518`*^9, {3.6153256235418167`*^9, 
   3.615325644074677*^9}, {3.615325730297449*^9, 3.615325748330233*^9}, 
   3.615325869445437*^9}],

Cell[BoxData[
 SqrtBox[
  RowBox[{
   RowBox[{"-", 
    FractionBox[
     SuperscriptBox[
      RowBox[{"(", 
       RowBox[{
        RowBox[{
         RowBox[{"-", "b"}], " ", "c"}], "+", 
        RowBox[{"a", " ", "d"}]}], ")"}], "2"], 
     SuperscriptBox[
      RowBox[{"(", 
       RowBox[{"a", "-", "c"}], ")"}], "2"]]}], "+", 
   FractionBox[
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       RowBox[{
        RowBox[{"-", "b"}], " ", "c"}], "+", 
       RowBox[{"a", " ", "d"}]}], ")"}], "2"], 
    SuperscriptBox[
     RowBox[{"(", 
      RowBox[{
       RowBox[{"-", "b"}], "+", "d"}], ")"}], "2"]]}]]], "Output",
 CellChangeTimes->{{3.61532503575928*^9, 3.6153250492170773`*^9}, {
   3.615325109195457*^9, 3.615325119328861*^9}, {3.6153251543721523`*^9, 
   3.615325196955284*^9}, {3.615325254430235*^9, 3.615325282308033*^9}, 
   3.6153253579311953`*^9, 3.615325396977257*^9, {3.615325459977042*^9, 
   3.615325469509162*^9}, 3.6153255667839518`*^9, {3.6153256235418167`*^9, 
   3.615325644074677*^9}, {3.615325730297449*^9, 3.615325748330233*^9}, 
   3.61532586944811*^9}],

Cell[BoxData["0"], "Output",
 CellChangeTimes->{{3.61532503575928*^9, 3.6153250492170773`*^9}, {
   3.615325109195457*^9, 3.615325119328861*^9}, {3.6153251543721523`*^9, 
   3.615325196955284*^9}, {3.615325254430235*^9, 3.615325282308033*^9}, 
   3.6153253579311953`*^9, 3.615325396977257*^9, {3.615325459977042*^9, 
   3.615325469509162*^9}, 3.6153255667839518`*^9, {3.6153256235418167`*^9, 
   3.615325644074677*^9}, {3.615325730297449*^9, 3.615325748330233*^9}, 
   3.615325869451263*^9}]
}, Open  ]],

Cell[CellGroupData[{

Cell[BoxData[
 RowBox[{"Plot3D", "[", 
  RowBox[{
   RowBox[{
    RowBox[{"Sin", "[", 
     RowBox[{"x", " ", "5", 
      SuperscriptBox["y", "2"]}], "]"}], 
    RowBox[{"Sin", "[", 
     RowBox[{"5", 
      SuperscriptBox["x", "2"], "y"}], "]"}]}], ",", 
   RowBox[{"{", 
    RowBox[{"x", ",", 
     RowBox[{"-", "1.1"}], ",", "1.1"}], "}"}], ",", 
   RowBox[{"{", 
    RowBox[{"y", ",", 
     RowBox[{"-", "1.1"}], ",", "1.1"}], "}"}], ",", 
   RowBox[{"PlotRange", "\[Rule]", "Full"}]}], "]"}]], "Input",
 CellChangeTimes->{{3.6153458884847183`*^9, 3.615345954066979*^9}, 
   3.615345985770969*^9, {3.615346075495479*^9, 3.615346276162806*^9}, {
   3.61534691214198*^9, 3.615346946017671*^9}}],

Cell[BoxData[
 Graphics3DBox[GraphicsComplex3DBox[CompressedData["
1:eJx0vXm819P2xx9FhiRJyFCIoiip0LSjrkLIcEkSN4SoiGvIlDQYikQJUaQB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   "], {{
     {EdgeForm[None], GraphicsGroup3DBox[{Polygon3DBox[CompressedData["
1:eJxFnQXYFcUXxu93e+PuLip2YGFgd6EgdqAiKIqBYAeKmAhiotjdjVjYiS2C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         "]], Polygon3DBox[CompressedData["
1:eJw1nWO4JEnXRbPq3rpl9Nj29Ni2bdu25x3btm3btm3b7vF8a/Wu70c+FZGB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         "]], Polygon3DBox[CompressedData["
1:eJwt13m8j2UaBvDXknOO8zvOCZVEtkLqZJ8s5Rx7BtkKqRBhiISSBslWtJii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         
         "]]}]}, {}, {}, {}, {}}, {
     {GrayLevel[0], Line3DBox[CompressedData["
1:eJwt1Ftoz2EYwPHH2GaOM26YsI25EBdSyHklMWaT8zmHOeR4oeyCZqyRsxxS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       "]]}, {Line3DBox[CompressedData["
1:eJwVzbkuxHEYheFPFBLLGFHp7Ps9aCiQIFqVQRTEXlk7jP0SUFIQxFCplDRK
jWXGfg88ijfn/N/z+2aqUpP9E3kRMYrjooiSRMQ6EjgrjpgvifjVBwoipkoj
VvU1XNjKkxFpVOrn2Pf2AO245xdkFT/tLu1mA538Jbdoq5ZP8hDPuLVVIMMv
+c5zV6N36IV8Fwb1rN+p5XPym3vhXpFCL5d198D36JvYwpBtGSd8ndsjb974
dwzzp3w9P+b7znaPET7Dr8gG24dtGzvo5ifkLhpts97PIL8sos3Wqt+gydbn
TQv3iHH9ivuUzfJL/vBZ/zHnfU5e86V88v9O35N/g2U7Og==
       "]], 
      Line3DBox[CompressedData["
1:eJwNzrkuBGAUxfGjkEgsMx7BU+AdjIRIUJrKFiqDKCydaFDwFMQU1soy9u0J
tBSCRIGG+BX/nHPPuTff11ae7J2oS9KNx8akUEg6UcRgS/LTlGwWkwfdNz8g
+6IbsnvZEr9qt741WadruJPP2JvFFJ7sTtMKbnV/dsZl/eYyP4QbeY3O0Q7a
jmt+zN4Lf8WP8s98D700f3q71Jz0NSQX5kXzB070R/JDnMv36QHedce6PX4X
Nd2OP1QxIn/TL+BM/uudYdkynZedyqrmV77L7babLazo/wEmqzXx
       "]], 
      Line3DBox[{3025, 3769, 3770, 3674, 3901, 4309, 3122, 3432, 3980, 3981, 
       3759, 4323, 3123, 3433, 3982, 3983, 3764, 4324, 3124, 3762, 4107, 4178,
        3125, 3846, 4109, 4179, 3126, 3030, 4180, 3127, 3032, 4181, 1912, 
       3034, 4182, 3128, 3036, 4183, 3129, 3038, 3899, 4184, 3130, 4016, 4065,
        4376, 4168, 4064, 4067, 3131, 3765, 4051, 4369, 4166, 3675, 3902, 
       3132, 3434, 4110, 4185, 3676, 3903, 3133, 3435, 4162, 4358, 3987, 3766,
        3771, 3134, 3989}], Line3DBox[CompressedData["
1:eJwVzrkuRHEYxuFPIYM5M4zeMkuvUYlrsIyllejNULkRV0EQpuAGLKVtIiJi
a5DYZqP0KH55l+/9n5z8crVc6YqIJTynI4rZiFx/RIkuZiI6+OXb9HQg4skm
L2dtCnRB38IP/+FewqPNiJyxGaXz7uP6LdR0Hd2DTR+fII05m8FcxD6/h3v3
I3qMNe8m6QTu9KvyG3/LV/lX/oav8OupiGt+hX/R1/l2ElH2/U1dgitdyq0X
PZh1e9e3/deu3KKXNjXaLTfcxjBj19Tt/Hf0wqapG+bP3YuYlr/lbZsvemZT
0J9gSG64T+GQ/8QBNmz/AOEvPFw=
       "]], Line3DBox[CompressedData["
1:eJwVzzkyA2AYxvE3lQJhLIlWEVvlAGbsQquxJgwtyYwLuIPCEo6gMpYZY+9c
QKcTy9ATYvkp/vO8z1J8X/tScbKQiIhFPNRGZJIRhw0RHXSqPmIDTfwrThsj
VviK7gufmOZT8n002/TXRazKznSb/Pn/Vnanz7tbZAN8zn2BLf6Szuqr8hN+
kB7TPtkclt1DsrL3Zfl53MuGZY+yHP/Gr9Enfr0m4pnm+RGbF/c3/UFJNkq3
7XewixIW5L/yVncKY+4r77rGDcr6XoS/dfJpm6xNgc/Ib7Ene+cT6LLpxrhN
kT/Qf9AjmwqdQY++jZ+wqbr/AEctOYE=
       "]], Line3DBox[CompressedData["
1:eJwVzzkvxFEUhvGjklhHopBgYgoRe3Qi0YmotToy0fEJhMRW2vd1vgYFphOS
0ROFQmnfhkz4Kd485z7vPfc/kxoeHxwriogRyZdGtFVEZMoiGssjDvHKeT4R
US9f+iz/Kwe6H9zHAs7p66TT/Q7JyZ4updvFWd2n/R1zkssXR5zhB5fRbfO1
zlt4iu/8CWZ1m1yNeQPbvdtQGdHNl1ZFHJvbdDfYind4LW/2q/Ut3JFz8///
sdMnr7okt+69Ue+t4QzfKy+6Vec0v4LTXNrdZ/4c+2VAvvkeeeJLfGfZ3Uk7
SziFj/wE3rqzyF2aFzBn98L8oO/S3UuV3zYkCSnomvAPfWU9xQ==
       "]], 
      Line3DBox[CompressedData["
1:eJwVzzdOQ1EUhOFjkgOOS0Ai9SQHbFiDqQHJDTYgKEg1YSuIDlgEFZgMEngT
NNDzveLXzJ055753Jzr77b1URHRQyUdUixFTpYgabRQiPvCOu3JEWf/KL+re
aB0v+HJez0aU9PP8pP0Fuqn7sTfMD6Gof5LN8c+0hnv9I/2U9WnBzAq/ihNd
VXYryyPrfIwlWUvfxLj8T5blczhMOuTkA3mTP0BGl06+kczqGvwyNnTXyduQ
kd9g2v//Os/SGaRl52Yv0EveUonYle9gTPdA+ziys0bbGJVv05TZlnyL76GL
Ed2l7NRdZ+higG9c6f8BDPoskw==
       "]], Line3DBox[CompressedData["
1:eJwV0Mkug2EYhuHXRiJatOaxuqI4ApEYqmYbcQBiIyF0hToAp2JYSrB0AmIj
MVdrWHEAluKyuPO+z/1835c/f3a9uLJTExEbyCQiphoico0ReTOfjKjixb5V
F9GnX7IvY4qv4LgpIoteXVl+xST6uSO82Ht0C+4sYkL+4p/NJ3TrHv/v6G75
DMblB5z4jnuzy5k0X8KBPO/sHDr5HHeDhFzSfZof6NB982/2d+zr6s1LbhDt
+hl5Fnu6Cy6FNv4Mu1yffI47eytXcXbVN1XNTfzohuUhtOivzGQqosBv24vY
QbPu0PkqP4Ix7xXkaaR1A9w1RuVarP3/R/MXZZx64w/G+DUz
       "]], 
      Line3DBox[CompressedData["
1:eJwVzLkuBGAYheGPKEhscwl6Q5RuAAWDEUs9BRWjsZR2gsa+lRRuQGILM5bh
RiwJEgUqEc8Ub87ynf+vy2TTIyURkcFjZcR+dcQB9jCKHl1/TcRqbcQDn+dz
aEJa7qN/br20QR6gKbkZSb6x2KPbXx26H36Xz6JgPyFPYhxliYix4lY/7J6k
K97c0zt86NqqIirslugihnDrtuO2bPvk/aAur3ulx7pW+u7+hht9Fz71YVvP
59Auf8vbNlu41i1494x5vKBg82VzxF+5z9FZnOk3vTnRbdB1XPIzbr/lES20
Uz6k5/TUfpqfwoWcwpo3CZT6/x9vUDwB
       "]], Line3DBox[CompressedData["
1:eJwVzbkuBGAUhuEj0UgsQ7gAF4CxXICWhohtplQoidIaSxS2GXqCiDHiFrgA
QowltpBQWls6HsWb75z3nPP/tQPDXUNFETGIp9KItbKIfHnEqmxHmjuoiPhN
RKRkoz4tk/jmmmQLmjGPlPkhP6fOu3/Uz6hnMY0pdJr/yBH/JM2z+gd5j3F+
AmNcKybV/fyet+5kPZdBzm0XbrkdmaiMuLBbwCVu+FH5ZbZvv819FhmM8X3m
L3wdrtQr/DKu1b3/PV+QDbhAh/7b3bb3tnDOLdn/QHFJxKfs4d5lDqfqRblp
99ltDc64I2xw6zhWV/OjeLW7gBOuG2/qXVTZ+wOrNkEu
       "]], 
      Line3DBox[CompressedData["
1:eJwVz7srBXAYxvFXlAEHHaKzWa06Z/En2BiP63G/FyOyyMw/YBAJx52NhVFR
yqWIKGIhm9HnDN+e932e5/3VryE32TpRFBE5vJZHrCQisvQS7di0v1VFNCJf
Zq+I+EaH7AqdOJP98LZQq79dmGmXbJV202udpHnHG6elETe8Huza8/oz8pz9
Fr3Y46d4s+izr7vtp3W0uDIizV/Gnfmdv8b/KOTVEftuP81tvC/6q5dBiW49
b4C3QQfpE3/KfOBmyP6IYSS8c65/yL+gf3ppOo8M7nEkW6APSOqPuFs0j9Jp
bx7Lm93NYYyXlY3TE34TbwnP9hb/f6E1blL4By4mOzE=
       "]], 
      Line3DBox[CompressedData["
1:eJwVz7kuhHEUhvGjUtgbiYzGpbiFCRrbREE3g/nsjJJINJarsC+xM3RKhUYn
SCYRxUxoLIXfFE/e8z7nfJP/dAzl0tmaiOjFR33ETkNEBVnzM3Io67tYa45I
NUbsmVeaIkbttvQx+WDXaj6pixjXXzDMfbs75fZ982O+4V7t8jjjD/j72og3
PcGhfs6n3BUwwZUwiQt+gyubt/1WRa7rl3yfvoR+rOpXGDBPuenyrmn56Paa
T/QZvVuOcL/Vd/EZ+YdoiRiUs26K/KabT3OP+y95y3Vyi3hyN8cty3nZ5ubO
vmh35L8scO8oVN9sd8y1y38olz3R
       "]], Line3DBox[CompressedData["
1:eJwNzrkyA2AYheGTWIJsFMwwo3An1gZVbkASasvo0FluwDKMwUUoU1qvgt7e
RsNTvHPO9/7rVHujsV5I0kCtmjzXkifU9SJuh5MtuVxJJuvJobzkKtySXpWr
5iIenXvAEHeGe/1UltG2XkBHH8AJjtHhBuWBu/rlUSkpyT58lJNt6z/efddH
R5Jv/RUvGDO/8YvOrpln0bV/Ti5gHi1/aHHBij7DTaOpN7k//U7fQa83b8zX
KLn7Su67u4e/sPfLvGffL7fJnXOf3C7X5cb1CfwDhPoquA==
       "]], 
      Line3DBox[CompressedData["
1:eJwVzjkvw3Ecx/GvsIgzddRRadHNZulDEEcNxo51jCQegGCgda2uKh6GBKsj
MfMMTAa60cHrP7zzub7//jpe3lhab4mIEia7Iq7RRB15nHRG/NLHZOuNmKBX
uO2JqNG37ohjN5+2aWR1RTlHj2hdl+EvcYExrOraMMyfY7A9YoQeun9IMs6w
62YIaf7ANpC8LTe8nUW//NUR8af7ke8wj6a8QBdRxJr/WPX9h36Zn9PNYoWv
6N/1Zf5Z94SZZNO1os8bNfqt23KTkkf5DHb0Bdzw+37n1b5pT+u2ccqXsGd7
sd3zU/QfP74wZQ==
       "]], Line3DBox[CompressedData["
1:eJwV0EsuA1AYxfGvtDRRyhJKIiZo69EFWIDHmIkBMyYWYR19edbYgFE9K5Gg
CCswN0Px6+Dkf875vntzc3Pr2ytbiYjYpOJgRJMehiLKmYhxvoKn2YjOcMTX
QMQiv0xLlB2JaOG3fgOrdsuY1qfs1/gLd/yYn/N9uozZGV+z29FndQ1atTdB
v7oFeZfe7dXtVXAPL81z/KfZkzfOyI84i2+6P2fb5nPyM85jHUe7bzMfwyvd
vruq/AF+6O/dEfy12SFO4o6+nxJyGss0pT+S2/YLVKQbXWAy7e38sXlCvuV7
un/oXIVedNO6NcrTq5ynXjtN85YuKTfkAn+CKfmOL+E/YKU63Q==
       "]]}, {
      Line3DBox[CompressedData["
1:eJwVzb8rBHAYx/HPlfxcjHdX1O0Wv5KIUsrdQjomGezYTDIptyrK7z+AOgbK
bFRmJmU3OBMWXoZ37+f5PM/3+1TWNhc3CkkW8NueNLuSazx0JhXUepNXvuxI
brqTD/2VelB2y2P8Jps2m8K4fsj7YWzLZ/Sj6hHMqid4Ejtm8/pHfzxxHatY
+r8rWzff4joP8FFPcowV/Qmf4gyfbn7LWlzUl1DGlxsv8ndvf9R9sn7syop2
yyhh372qvIaG2Rwf4gDPZk3ZORfsXnALd7J7bpM1sIdl+3/roSts
       "]], 
      Line3DBox[CompressedData["
1:eJwV0D0vgwEUhuFjUiwsFhO7yexHlIiFoAOCaFpDu/gBbKIDovExtUQxICkb
EqGxCIlEwm6QMOhgcL3Dnfs8zznv24/eTHZosSUiJhCtESdtEaft4OtURJ5L
8mdnRM78rqvzme6S7+QiV+w3dAXzh+6GL+Rbvpe3zFU3Yx0Rm+ZB1HGVvAdr
dg/uMvZTmERaLukbPIwe3y+LtK6PCxgx9/Myxs0DXPZsd1fEDu9iD/to+pw/
N7+ck/NYSm50z95f1U/LFZ7DPB7xY7/AL24OecbNAX/J635fw/4p+Z/wqqvZ
zbo54m/53H472aGMN92q3TFWMOr2H5mdPms=
       "]], Line3DBox[CompressedData["
1:eJwVzr8rxHEcx/E30rm7XO5QVgtGiz8AZdGVGCn5hvGO7QZWScqky2Jg8KPO
JBYZDYoysRjcQN9BjJg8bnj1fL1e7/f78/0OJtXZSltEJNSZibjMRgx1RdzR
ME33RIzkIrKUo4adMbzAslmeb7rJ5COudAX5GmfMRnU1etf9yCl+UFFXoihG
PNhN3T9iyayXXu0+y5/6FzzUPfmX5dadmy1cks8wwXM8pQGzE6zqxnENF701
wa/zc955894G38TEbNI3NuUp/NJt89+4YrbDl/W/8j7/h3U8MmtvkTqo6t0K
HfPz9u/N97BbrmMBD3CBGvwqpnZqbvrkG+qnXfkW/wFV/jUG
       "]], 
      Line3DBox[CompressedData["
1:eJwVzzkvhFEUBuAzyIwlGD9BiR+AWqGzTGEpMGYSCYUtUdoSWzAjGhEaW6KT
+AVaSgqNxliTKSh14lE8Ofe+73du8jXnZjLTiYjIk0xFtNZGtFGqiUiZSZ7S
ES3VEYm6iAqCKn7lleaLb5555UdWMuvlDTSyKHvzXpM8Tbe3OuSdLOvazT2K
lH2X1x/IH8xT359wxpdsRb/Kh26CYdm3+4JzmXXnNe7kXd4bsDfIku5Y9u4f
b903dVvsyD/l47IsOXrs39PLhu7QN/3O2/Rxzi6F/7P+Qj9nL+O9WXOeEd0j
o1zps+YRY1y7X9qbdJ7ixr1oZ8h+wdznD+ndNrI=
       "]], Line3DBox[CompressedData["
1:eJwVzr8rBHAYx/HH4HBn4E+wGZjMzkDyowxncBRyxRExkAGDKEcRGSiUwY8z
imKUKEz+AyXFcPwNvAzv3s/z+Tx9+9blZjLTZRExhoqKiJuqiOtkxC0/VUbM
8Z79uyZi1lyfimiwN6JJn7Bv6sq5Wpb6N5IYwq9ukIdxqD/CjuzTW23mVrSj
2X4nT/O7d1/9pWTOm/flH3zq7gRnWNE9y1f5S9fi/TQStRE9+iz6UdIV3Fy5
XeNRN+fyIn501/J5XkaH/kXeyVv2bj7Wr3MXNpBBLwryAzfj7vOYQJ/8QZ7l
om6A+3FhHuFHXY4v7YvuF7CESdkbpnCv2/n/u39u8y7+AGRNOCc=
       "]], 
      Line3DBox[CompressedData["
1:eJwV0L8rxHEcx/H3LccRiZKBopTCJGFhMpCBblJCkQx0BpNyksWglMvAH+DH
jUwyMQlFqct+6TJIyuYojxuevd7v5+vbu0/fjoW1dCYREUuYroo4RrYm4jUV
cVkdkZMF+4F8bIhI6w/xYs/r23QnfKuc4PdRNv9gtTbiT7ciR/k9PPDNKPFz
chYj/C6a3NzmP90t2YewgyPug3vWP6GP28Q1X29/1025M4kuvsCvyy/7m27L
N1nc8e18pvIOe1F3wY3LFm4FKX7MPihzuns5gEbdMpLmYX1Rd2u+QR2/iIR5
g+/X95p7UM3P44ov893I8+f4TUbM6Dr9n+/KG3DKn+EE7d7/Dxc/OFc=
       "]], 
      Line3DBox[{1881, 1946, 2967, 2777, 2776, 2699, 2692, 2694, 4330, 2693, 
       1877, 1942, 2563, 2562, 4314, 2218, 1870, 1936, 2559, 2558, 4313, 2204,
        1863, 1932, 2966, 4372, 2192, 1856, 1929, 4347, 2806, 1850, 1924, 
       4373, 2974, 1844, 1918, 4210, 1838, 1912, 4206, 1827, 1904, 4202, 1820,
        1900, 4243, 2130, 1812, 1897, 2982, 2981, 4375, 2116, 1806, 1892, 
       4368, 2947, 2618, 2620, 2619, 1802, 1888, 4234, 2610, 2612, 2611, 1793,
        1884, 4307, 2528, 2527, 2597, 2596, 2854}], Line3DBox[CompressedData["

1:eJwNz7Evg1EUhvHDQn2DGowGid1UA4suIiERhg4VERIDUo1gMFl0EZWQlEGq
i80gqcWgtQgRGiSmJv4Ig6Sj3/DkPec+5577fcOrxYWtrohYRr4n4hLrSUQ7
FfHTG1GT7b6IK9lKR+T4C+w528WNmXPuW/3HV9Rz/Cnm7Sk4r5n5lNf8l/zA
NF/GrJkZnJlJBiLeuRbekOWPUHWvxB9iQl/CjrOMPMAocvp9WZQjchub6iFZ
QNobZRxjUL+BMXUGU/b+mm168xEN9PNryKonccKPm3vxf/f6Z5nwK1i0I+Xb
w9mrmYZs4gHd/K27SzJvrsM/4Y6r21OXFfkP8lU1Tg==
       "]], 
      Line3DBox[CompressedData["
1:eJwV0L8rBHAcxvHPUXd+DM6kMzg3UQwm5Q84g0wsTEopFhZlIHeXyeTHImW1
yGhAWa7zo1BnMaIkmTGIw+uGd8/38zzP5/utb256YWw+EREzyDRFHDRH5Foi
9lIRneYPfGI9HVFLRvTI92V9vB/UcKR/zN+h/eZB+qTfwGtEGQM4tXfGX3ZO
YQVNONG/onla0anqjLhnszViG1vI8Gf5VTohu9a/wS3u+AU6yX/Bos4zr7e+
Y35DmzyNQ37ZO1XnOf4SdnlrukN4RUVe4p3TYW9f0Et0YArvOg/yb3cU5EXk
eSX6JW9rj8g6b/BGkTB3m5P1/5L/4g/jskf3ZOs7si66iiIKuMc/13g6ww==

       "]], Line3DBox[CompressedData["
1:eJwVzb8rBHAcxvGPwv1ydbKhE5vh7BZKOHUdksmoCMVZTtjuJvtlY5Hdpi6L
uqxkkVj9AUIsfr1uePc8n+fzfL7f4dXK0k5HRKxhIBkxkorYxmkiYtD8iTPz
bS7ii//tjmiaG+mIvLnQztC0H5P98Sm3BZ0qLvgD2olDdOFSr0XH6ZX9ndsJ
dxt8H9bNN7QkS+tl0G8u6m/a3fNzfI88i2v+TV6mK25KtKrzIhulW7JXvTc8
yN5pS2eKPtvv209nIhK9ETP0HA3U5HWcuDnSm8QH0nrb9hXsYla27K0in7T7
MS/y81hA2VynVe98+3eYP27fIKu/Z8755wl579R0hugj/gFC5jQt
       "]], 
      Line3DBox[CompressedData["
1:eJwVzqFPwmEQh/FzzonCJpvKtLgx1KToDCYSjQ02ZG42ApjVGZz8KMxAsWkx
+idYDJqY1UqDpk6DZKsfwrPn7nu3e99867xxNhMRR9hMRWwvRhR4jpvzEU/Z
iFk+kKVkLfWtLMPP2ElHJPpd3kMRWfmS3TIG6rH5x0LEp/4LOdk7hvJveWd6
AxuyLv/aWeZL/RYu7CV8wvvcQ1N9yB3/StBXlzBBX39jvuL2KsqyKv/xm/ze
fE3f9s46V+Sn6po3w+zHziPfyeu40qf1x+YP03/gWvYie8XIjTFGbvwDnEon
hQ==
       "]], Line3DBox[CompressedData["
1:eJwNzj8oxHEYx/Hn6ur8z49y5U/cgDCZDFJKFpsrZbEQFp2U3HAo02UyMMjk
WO2GG2SwmYRNGS9/znpMXsO7z/O8n+f7J7e6nS+kImIFw01ojhhtibjKRDzo
f3HbGfEn09yd+Y2caI0YQzqJGJfXOMa0vXbnN+ycOJfIIn8vO+zWzD7wiSy3
aedR1tz7zdUxqN/iX+UXv+/8AUb0h3LH7MfemrrELesnZcHbs9yR+oKbku8o
8Yl7qlyXnOHmZV2WzXrUWczpG6jYO+N7uT4scLtciqvgVL+IZ7Mi38bt+U+/
fsn7A/IFT2br8hzddqoYUl8ihzf8A7lCMB4=
       "]], Line3DBox[CompressedData["
1:eJwV0D8vQ2EYhvGHpUUHEptI0AVDxUK3xlhpiI6NJo3YcCz4AHwMwcbAUCEm
xFSjhMGAncEg1CChfh3uXM/95z3DGV5aLycdEVGli3TEdnfEOT7RGX33RjzK
gtL8SE9ECjv7IrLu366IAV0rFbEr/8OMblO3QV+6BD/xx7eauIxvdjv2r9j0
jX55Tf7CV9zPWMY1mwWs6FbdH7YrON7uZVV3Sb+I7/ye+85dxAebWbzHG13B
2zndLV/CBl7L8/IZ/oov4CVO4bS38/pTPu+u4yTm7Cf0Y7hFDZsjXU52iIls
lIba/8u+qM/igW5Qto/H+hP6B7Q+M2Y=
       "]], Line3DBox[CompressedData["
1:eJwVzr0vg3EUxfHbibYLogyViLeFAYOkTE2sJKKbDl4nQysxGjvjX2BD0sVL
bKSDRLeGio2dxdBWJAYfw8n5nnPvfX7PyFZ5tZSIiDW67Y7YSUZUUhF9+IZ6
aVt33RPxhffNUryQjkjylv5Z90TH8q/dI17VN3mnKyJrtyK38RD+sfOJX3Xf
+ANn3Hfwpu5dbuE3Pmh/gIr6DN+lfpoyK+g2vFFzu84v5AZ/MSvyJq/p8r61
Ii/wum4ZP/J5eRHf4zw/sHuHZ/U5+Qof6ubwJZ7h095a0p3/Z3zGJ/zPpJtR
8wezcbxHp2bDuhNelseoSn+XzTI3
       "]], Line3DBox[CompressedData["
1:eJwVzTsoBWAYxvFXnDgspJgtLpNcJpdBKZtBzjEwuR0ThZLJwuCSLJQUyXEW
yqQoSuwWC3IZsBIrg98Z/j3P+7zP+301w1N9kwURkcFVScREMmIf1fwlqrBj
ziBXHnFiniuNmEeOP8ZhXs1f9ht69+Y0zSLBr9MiukpT2ObH9MfxVxyxZV5y
+8uv8T9017zMf/M9bhb4Qf0R+btsiH+j3Xazdh/ylGyG76fT9NOuoiJiscx/
+T/oKO2kezpHbu7MXXqP3uqQP9CEm3a+DQP2t9jUTef/0V2R3+it0krda76V
b0aHTqNOC38uv3DXxJ/xSVqCXtmz/1/xhBcUeqfOLqtX740D2iCv9dYp/gGM
PDmk
       "]]}, {}, {}}},
   VertexNormals->CompressedData["
1:eJyUfXVUV9ESLnZ3dwd2t45it4id2N1id3crKgaKYieIiYMCIiYNKkh3GajY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    "]],
  AutomaticImageSize->True,
  Axes->True,
  BoxRatios->{1, 1, 0.4},
  ImageSize->{402.6925090106427, 171.11738350732128`},
  Method->{"RotationControl" -> "Globe"},
  PlotRange->{{-1.1, 1.1}, {-1.1, 1.1}, {-0.9993995497788725, 
   0.9993995497788725}},
  PlotRangePadding->{
    Scaled[0.02], 
    Scaled[0.02], 
    Scaled[0.02]},
  ViewPoint->{-1.760126307743618, 2.8591885279772074`, -0.4207093322857617},
  ViewVertical->{0., 0., 1.}]], "Output",
 CellChangeTimes->{{3.615346261028924*^9, 3.615346277897931*^9}, {
  3.615346929574892*^9, 
  3.61534694724934*^9}},ImageCache->GraphicsData["CompressedBitmap", "\<\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\
\>"]]
}, Open  ]],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.6153462586916924`*^9, 3.615346258754003*^9}}],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.6153462056303053`*^9, 3.615346206032742*^9}}],

Cell[BoxData[""], "Input",
 CellChangeTimes->{{3.615346090733872*^9, 3.6153460908171263`*^9}}]
},
WindowSize->{1366, 648},
WindowMargins->{{0, Automatic}, {Automatic, 0}},
FrontEndVersion->"9.0 for Mac OS X x86 (32-bit, 64-bit Kernel) (January 25, \
2013)",
StyleDefinitions->"Default.nb"
]
(* End of Notebook Content *)

(* Internal cache information *)
(*CellTagsOutline
CellTagsIndex->{}
*)
(*CellTagsIndex
CellTagsIndex->{}
*)
(*NotebookFileOutline
Notebook[{
Cell[CellGroupData[{
Cell[579, 22, 2144, 42, 28, "Input"],
Cell[2726, 66, 25409, 420, 444, "Output"]
}, Open  ]],
Cell[28150, 489, 426, 6, 80, "Input"],
Cell[CellGroupData[{
Cell[28601, 499, 603, 19, 51, "Input"],
Cell[29207, 520, 1587, 54, 51, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[30831, 579, 681, 19, 28, "Input"],
Cell[31515, 600, 17283, 294, 238, 10235, 177, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[48835, 899, 411, 12, 32, "Input"],
Cell[49249, 913, 194, 3, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[49480, 921, 1116, 30, 35, "Input"],
Cell[50599, 953, 15952, 269, 201, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[66588, 1227, 406, 12, 28, "Input"],
Cell[66997, 1241, 315, 9, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[67349, 1255, 396, 12, 48, "Input"],
Cell[67748, 1269, 94, 1, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[67879, 1275, 284, 7, 28, "Input"],
Cell[68166, 1284, 319, 11, 59, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[68522, 1300, 128, 3, 40, "Input"],
Cell[68653, 1305, 114, 1, 28, "Output"]
}, Open  ]],
Cell[68782, 1309, 400, 13, 56, "Input"],
Cell[CellGroupData[{
Cell[69207, 1326, 477, 14, 47, "Input"],
Cell[69687, 1342, 10836, 187, 230, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[80560, 1534, 2390, 62, 130, "Input"],
Cell[82953, 1598, 8596, 148, 242, "Output"],
Cell[91552, 1748, 16643, 280, 242, "Output"],
Cell[108198, 2030, 16326, 274, 242, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[124561, 2309, 596, 19, 56, "Input"],
Cell[125160, 2330, 113, 1, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[125310, 2336, 832, 25, 56, "Input"],
Cell[126145, 2363, 11085, 190, 229, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[137267, 2558, 3905, 113, 174, "Input"],
Cell[141175, 2673, 21927, 364, 175, "Output"],
Cell[163105, 3039, 20493, 339, 175, "Output"],
Cell[183601, 3380, 29195, 481, 84, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[212833, 3866, 727, 21, 28, "Input"],
Cell[213563, 3889, 28225, 470, 231, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[241825, 4364, 1859, 51, 44, "Input"],
Cell[243687, 4417, 12785, 220, 372, "Output"]
}, Open  ]],
Cell[256487, 4640, 69, 1, 28, "Input"],
Cell[CellGroupData[{
Cell[256581, 4645, 237, 6, 28, "Input"],
Cell[256821, 4653, 200, 5, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[257058, 4663, 1941, 38, 49, "Input"],
Cell[259002, 4703, 33035, 547, 359, 19305, 323, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[292052, 5253, 69, 1, 28, "Input"],
Cell[292124, 5256, 69, 1, 28, "Input"],
Cell[292196, 5259, 92, 1, 28, "Input"],
Cell[292291, 5262, 2091, 72, 46, "Input"],
Cell[CellGroupData[{
Cell[294407, 5338, 5442, 142, 183, "Input"],
Cell[299852, 5482, 28687, 478, 70, 21478, 359, "CachedBoxData", "BoxData", \
"Output"],
Cell[328542, 5962, 28584, 476, 129, 20009, 335, "CachedBoxData", "BoxData", \
"Output"],
Cell[357129, 6440, 20383, 340, 133, "Output"],
Cell[377515, 6782, 17414, 292, 78, "Output"],
Cell[394932, 7076, 11601, 197, 242, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[406570, 7278, 94, 1, 28, "Input"],
Cell[406667, 7281, 21670, 358, 129, "Output"],
Cell[428340, 7641, 21752, 359, 133, "Output"],
Cell[450095, 8002, 18783, 311, 78, "Output"],
Cell[468881, 8315, 12970, 216, 242, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[481888, 8536, 827, 25, 70, "Input"],
Cell[482718, 8563, 36074, 600, 415, 22906, 382, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[518829, 9168, 680, 22, 50, "Input"],
Cell[519512, 9192, 1029, 33, 54, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[520578, 9230, 237, 7, 32, "Input"],
Cell[520818, 9239, 205, 5, 32, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[521060, 9249, 414, 13, 50, "Input"],
Cell[521477, 9264, 213, 5, 32, "Output"]
}, Open  ]],
Cell[521705, 9272, 1024, 29, 85, "Input"],
Cell[CellGroupData[{
Cell[522754, 9305, 833, 26, 50, "Input"],
Cell[523590, 9333, 16228, 275, 242, "Output"]
}, Open  ]],
Cell[539833, 9611, 111, 2, 28, "Input"],
Cell[CellGroupData[{
Cell[539969, 9617, 122, 4, 34, "Input"],
Cell[540094, 9623, 116, 3, 32, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[540247, 9631, 759, 22, 67, "Input"],
Cell[541009, 9655, 18512, 313, 226, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[559558, 9973, 2260, 57, 172, "Input"],
Cell[561821, 10032, 945, 21, 61, "Output"],
Cell[562769, 10055, 1236, 32, 77, "Output"],
Cell[564008, 10089, 2202, 64, 97, "Output"],
Cell[566213, 10155, 3411, 103, 97, "Output"],
Cell[569627, 10260, 5549, 173, 197, "Output"],
Cell[575179, 10435, 8507, 270, 267, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[583723, 10710, 2874, 81, 147, "Input"],
Cell[586600, 10793, 451, 10, 31, "Output"],
Cell[587054, 10805, 730, 19, 32, "Output"],
Cell[587787, 10826, 312, 5, 28, "Output"],
Cell[588102, 10833, 2472, 76, 57, "Output"],
Cell[590577, 10911, 4622, 146, 99, "Output"],
Cell[595202, 11059, 8501, 271, 185, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[603740, 11335, 1851, 59, 102, "Input"],
Cell[605594, 11396, 146, 2, 28, "Output"],
Cell[605743, 11400, 146, 2, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[605926, 11407, 723, 22, 54, "Input"],
Cell[606652, 11431, 505, 15, 51, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[607194, 11451, 174, 4, 28, "Input"],
Cell[607371, 11457, 99, 2, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[607507, 11464, 267, 7, 28, "Input"],
Cell[607777, 11473, 17736, 302, 238, 9505, 165, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[625550, 11780, 287, 8, 49, "Input"],
Cell[625840, 11790, 129, 2, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[626006, 11797, 121, 2, 28, "Input"],
Cell[626130, 11801, 74, 1, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[626241, 11807, 807, 24, 46, "Input"],
Cell[627051, 11833, 144, 2, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[627232, 11840, 3834, 116, 209, "Input"],
Cell[631069, 11958, 1003, 22, 47, "Output"],
Cell[632075, 11982, 982, 20, 47, "Output"],
Cell[633060, 12004, 740, 11, 28, "Output"],
Cell[633803, 12017, 742, 11, 28, "Output"],
Cell[634548, 12030, 740, 11, 28, "Output"],
Cell[635291, 12043, 740, 11, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[636068, 12059, 922, 26, 49, "Input"],
Cell[636993, 12087, 33172, 552, 338, 20262, 339, "CachedBoxData", "BoxData", \
"Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[670202, 12644, 483, 14, 28, "Input"],
Cell[670688, 12660, 429, 13, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[671154, 12678, 348, 10, 51, "Input"],
Cell[671505, 12690, 833, 30, 53, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[672375, 12725, 676, 20, 80, "Input"],
Cell[673054, 12747, 187, 4, 28, "Output"],
Cell[673244, 12753, 187, 4, 28, "Output"],
Cell[673434, 12759, 97, 1, 28, "Output"],
Cell[673534, 12762, 97, 1, 28, "Output"]
}, Open  ]],
Cell[673646, 12766, 94, 1, 28, "Input"],
Cell[673743, 12769, 323, 11, 52, "Input"],
Cell[674069, 12782, 441, 14, 50, "Input"],
Cell[CellGroupData[{
Cell[674535, 12800, 1611, 52, 93, InheritFromParent],
Cell[676149, 12854, 1095, 34, 59, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[677281, 12893, 824, 23, 97, "Input"],
Cell[678108, 12918, 275, 8, 28, "Output"],
Cell[678386, 12928, 248, 7, 28, "Output"],
Cell[678637, 12937, 273, 8, 32, "Output"],
Cell[678913, 12947, 273, 8, 32, "Output"],
Cell[679189, 12957, 258, 7, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[679484, 12969, 4220, 102, 55, "Input"],
Cell[683707, 13073, 176, 3, 28, "Output"]
}, Open  ]],
Cell[683898, 13079, 2064, 65, 52, "Input"],
Cell[CellGroupData[{
Cell[685987, 13148, 2240, 64, 48, InheritFromParent],
Cell[688230, 13214, 246, 4, 28, "Output"]
}, Open  ]],
Cell[688491, 13221, 2079, 65, 48, "Input"],
Cell[CellGroupData[{
Cell[690595, 13290, 18651, 542, 302, "Input"],
Cell[709249, 13834, 1081, 20, 28, "Output"],
Cell[710333, 13856, 1458, 32, 30, "Output"],
Cell[711794, 13890, 1458, 32, 30, "Output"],
Cell[713255, 13924, 2943, 78, 48, "Output"],
Cell[716201, 14004, 894, 13, 28, "Output"],
Cell[717098, 14019, 894, 13, 28, "Output"],
Cell[717995, 14034, 896, 13, 28, "Output"],
Cell[718894, 14049, 894, 13, 28, "Output"],
Cell[719791, 14064, 896, 13, 28, "Output"],
Cell[720690, 14079, 894, 13, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[721621, 14097, 246, 7, 28, "Input"],
Cell[721870, 14106, 276, 9, 32, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[722183, 14120, 19730, 589, 333, "Input"],
Cell[741916, 14711, 1113, 34, 28, "Output"],
Cell[743032, 14747, 1632, 49, 35, "Output"],
Cell[744667, 14798, 1992, 60, 51, "Output"],
Cell[746662, 14860, 1738, 52, 35, "Output"],
Cell[748403, 14914, 1736, 52, 35, "Output"]
}, Open  ]],
Cell[750154, 14969, 162, 3, 28, "Input"],
Cell[CellGroupData[{
Cell[750341, 14976, 613, 21, 46, "Input"],
Cell[750957, 14999, 857, 31, 32, "Output"],
Cell[751817, 15032, 857, 31, 32, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[752711, 15068, 9036, 312, 138, "Input"],
Cell[761750, 15382, 1646, 60, 32, "Output"],
Cell[763399, 15444, 485, 11, 28, "Output"],
Cell[763887, 15457, 485, 11, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[764409, 15473, 938, 31, 63, "Input"],
Cell[765350, 15506, 32927, 949, 406, "Output"],
Cell[798280, 16457, 32913, 946, 402, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[831230, 17408, 651, 17, 28, "Input"],
Cell[831884, 17427, 122223, 1997, 454, "Output"]
}, Open  ]],
Cell[954122, 19427, 160, 3, 28, "Input"],
Cell[CellGroupData[{
Cell[954307, 19434, 1456, 39, 162, "Input"],
Cell[955766, 19475, 636, 13, 28, "Output"],
Cell[956405, 19490, 538, 9, 28, "Output"],
Cell[956946, 19501, 849, 22, 48, "Output"],
Cell[957798, 19525, 1096, 31, 69, "Output"],
Cell[958897, 19558, 491, 7, 28, "Output"]
}, Open  ]],
Cell[CellGroupData[{
Cell[959425, 19570, 696, 19, 35, "Input"],
Cell[960124, 19591, 229325, 3803, 186, 175679, 2922, "CachedBoxData", \
"BoxData", "Output"]
}, Open  ]],
Cell[1189464, 23397, 94, 1, 28, InheritFromParent],
Cell[1189561, 23400, 94, 1, 28, InheritFromParent],
Cell[1189658, 23403, 94, 1, 28, InheritFromParent]
}
]
*)

(* End of internal cache information *)
